Lecture 12

bull Field work (lab work)

bull Analysis of data

bull Short field workndash ex ldquoRapid rural appraisalrdquo

ndash Seeks a sketch of local conditions rather than an in-depth study

ndash The emphasis is on highly visual techniques that community members carry out amongst themselves

ndash This analysis of the data is carried out in the community

ndash Measurements are qualitative rather than quantitative

Field work (lab work)

Field work (lab work)

bull Long field work involves at least three field work periods

bull Allow an in-depth analysis of a situation

bull Time is available for quantitative analysis

bull Allow a broader scope of the study

bull Time is available for voucher collections

bull Prepare for field work (applies for both short field work and long field work)

ndash Obtain secondary information ndash maps floras census statistics etc

ndash Obtain permission of local authorities before starting fieldwork

ndash Review existing literature also local fora

bull The first field season

ndash Describe the field site including geographical location and map population size and distribution languages spoken etc

ndash Identify main informants study unitsndash Produce some brief results

Main field work bull Remember locating and obtaining

permission to use materials

bull Make sure to do everything systematically

Data should be stored for 10 years

Stick to the same units tools and scales throughout the study

A unique identification number for each collection

bull While in the field it is helpful to make

some initial analyses of the data

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

bull Short field workndash ex ldquoRapid rural appraisalrdquo

ndash Seeks a sketch of local conditions rather than an in-depth study

ndash The emphasis is on highly visual techniques that community members carry out amongst themselves

ndash This analysis of the data is carried out in the community

ndash Measurements are qualitative rather than quantitative

Field work (lab work)

Field work (lab work)

bull Long field work involves at least three field work periods

bull Allow an in-depth analysis of a situation

bull Time is available for quantitative analysis

bull Allow a broader scope of the study

bull Time is available for voucher collections

bull Prepare for field work (applies for both short field work and long field work)

ndash Obtain secondary information ndash maps floras census statistics etc

ndash Obtain permission of local authorities before starting fieldwork

ndash Review existing literature also local fora

bull The first field season

ndash Describe the field site including geographical location and map population size and distribution languages spoken etc

ndash Identify main informants study unitsndash Produce some brief results

Main field work bull Remember locating and obtaining

permission to use materials

bull Make sure to do everything systematically

Data should be stored for 10 years

Stick to the same units tools and scales throughout the study

A unique identification number for each collection

bull While in the field it is helpful to make

some initial analyses of the data

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Field work (lab work)

bull Long field work involves at least three field work periods

bull Allow an in-depth analysis of a situation

bull Time is available for quantitative analysis

bull Allow a broader scope of the study

bull Time is available for voucher collections

bull Prepare for field work (applies for both short field work and long field work)

ndash Obtain secondary information ndash maps floras census statistics etc

ndash Obtain permission of local authorities before starting fieldwork

ndash Review existing literature also local fora

bull The first field season

ndash Describe the field site including geographical location and map population size and distribution languages spoken etc

ndash Identify main informants study unitsndash Produce some brief results

Main field work bull Remember locating and obtaining

permission to use materials

bull Make sure to do everything systematically

Data should be stored for 10 years

Stick to the same units tools and scales throughout the study

A unique identification number for each collection

bull While in the field it is helpful to make

some initial analyses of the data

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

bull Prepare for field work (applies for both short field work and long field work)

ndash Obtain secondary information ndash maps floras census statistics etc

ndash Obtain permission of local authorities before starting fieldwork

ndash Review existing literature also local fora

bull The first field season

ndash Describe the field site including geographical location and map population size and distribution languages spoken etc

ndash Identify main informants study unitsndash Produce some brief results

Main field work bull Remember locating and obtaining

permission to use materials

bull Make sure to do everything systematically

Data should be stored for 10 years

Stick to the same units tools and scales throughout the study

A unique identification number for each collection

bull While in the field it is helpful to make

some initial analyses of the data

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Main field work bull Remember locating and obtaining

permission to use materials

bull Make sure to do everything systematically

Data should be stored for 10 years

Stick to the same units tools and scales throughout the study

A unique identification number for each collection

bull While in the field it is helpful to make

some initial analyses of the data

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Last field work periodbull Before this last field period perform

initial analysis of the data

bull Look for whatrsquos missing in the data or what you would like to explore in greater detail

bull Do not forget to say good bye and thank you to the community in which you have been working leaving it in a good

manner

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysis of data

bullThe purpose of analysing the data is explore different interesting characteristics inherent in the results

bullCharacteristics that the study units have in common

bullCharacteristics that the study units are different from

bullCategorization is the way that something is divided up into a set off of different classes

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysis categorizationbull Selecting categories

bull Categorization of the data into different levels how many levels

bull Value can be assigned to different categories

bull Beware of units and scales need to be the same

Categories of use

05

101520253035404550

Constru

ction

Med

icine

Commerci

al

Food

Firewoo

dCra

ft

Other

Nu

mb

er o

f sp

eice

s

Species used seldomly(not used presently)

Species used presently

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysing quantitative forms of data

bull The number of individuals and species

bull The structure of the data set

bull Quantitative data in social sciences how many inhabitants different age classes etc

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysis of data

bull Graphical presentationndash Tables and figures permits us to

present a simplified version of the results

ndash Can be used to report precise numbers or to illustrate a trend

ndash A trend might be better illustrated with a figure

ndash Graphs typically relate two dimensions such as quantity of time

ndash Graphs show trends or movements over time

ndash Use the program ldquoexcelrdquo free and relatively simple

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysis of data

bull An important tool for analyzing data is statistics a mathematical way of summarizing and interpreting quantifiable research results

bull Do your study allow for statisticsndash Must be considered when designing the study

bull It is important to understand when to apply each statistical tool and how to interpret the results

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Statistical analysis of data

bull Everything varies if you measure two things twice they will be different

bull P value -the power of a test is the probability of rejecting the null hypothesis when it is false

bull The null hypothesis nothing happens

bull The alternative hypothesis there is significant divergence or pattern in the data

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Statistical analysis of data

bull Various measures of central tendency describe important properties of a population of study units ndash Calculation of the modendash Calculation of the medianndash Calculation of the mean

bull The measure of variabilitythe analysis of variation about meansndash Used for establishing measures of unreliabilityndash Used for testing hypothesis

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Regression

bull The statistical model when explanatory variables is continuous

bull To check relationship between two variables

bull A number of assumptions the most important normally distributed errors

Can you think of data where analysis of regression could be useful

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Analysis of variance (anova)

bull Analysis which involves a range of discrete levels of categories

bull Fundamental question are there differences between means

bull Several assumptions underlying the analysis the most important equal variances

Can you think of data where analysis of anova could be useful

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

bull Other common statistics are the chi-square test correlation and ordination analysis ndash Analysis of co-variancendash Nested design different treatments are applied

to plots of different sizendash Correlation analysis to check how variables

vary together

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Qualitative analysis

bull A general analysis strategy advanced by three qualitative authors (Bogdan amp Biklen 1992 Huberman amp Miles 1994 Wolcott 1994)

1 A general review of all information

2 The process of reducing the data begins

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Qualitative analysisbull To analyse qualitative data the researcher engages

in the process of moving in analytic circles

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19

Qualitative analysisComputer programs ex NUD IST may help in the

analysis phase

ndash The program provides an organized storage ldquofilerdquo system

ndash Helps locating material easily

ndash However programs should not take the place of careful analysis of the material

• Lecture 12
• Slide 2
• Field work (lab work)
• Slide 4
• Slide 5
• Slide 6
• Analysis of data
• Analysis categorization
• Analysing quantitative forms of data
• Slide 10
• Slide 11
• Statistical analysis of data
• Slide 13
• Regression
• Analysis of variance (anova)
• Slide 16
• Qualitative analysis
• Slide 18
• Slide 19