sociological metodology quantification petr soukup

Sociological metodology

QuantificationPetr Soukup

Outline of the lecture

1. Data, variables, values in quantitative research

2. Data preparation, data entry, coding of variables

3. Presentation of data, basics of statistic (Quantification)

4. Advances statistical techniques – review

5. Statistical software

6. Data archives and its usage

1. Data, variables

• Variables 3 types

• Variables and questions

• Variable = 1 question ?

• Numerical data – necessary for computer

Data, variables

• Values of variables – for interval variables natural, for ordinal and

nominal artificial values (assigned by a researcher)

• Data matrix – rows (respondents), columns (variables)

• Technical names of variables (queustionnaire)

2. Open-ended question and problem of coding

1) Predefined coding schemes

Examples – ISCO, EGP, ISEI

2) Creating of our own coding scheme – example

Collapsing of categories

3. Basics of statistics (Quantification)

1) Frequencies

2) Central tendency

3) Crosstabulations

Basics of statistics – Frequencies

Frequencies – absolute and relative (percentages)

Interpretation

Example in MS Excel (data EVS)

Basics of statistics – Central tendencies

MEAN –arithmetic mean of values (sum of values divided by the number of values)

MEDIAN - the value in the middle of data )

MODE – the most frequent value in our data

Basics of statistics – Dispersion

Range – difference between maximum and minimum

Standard deviation – dispersion for interval variables (interpretation of standard deviation)

Examples in Excel

Bivariate statistics

Nominal and ordinal variables:

Crosstabulations – total counts, row and column percentages

Chi-square test of independence

Interval variables:

Correlation

Correlation coefficient and its values

Examples in Excel (EVS data)

Functions in Excel:

FREQUENCY – enables to prepare frequency table

AVERAGE – compute arithmetic mean of values (sum of values divided by the number of values)

MEDIAN - compute median (middle) - the values in the middle of data )

MODE – compute mode, the most frequent value in our data

MAX – maximum of variable

MIN – minimum of variable

STDEV – standard deviation

4. Advanced statistics - review

More than two variables

Usually called modeling

Examples:

Loglinear modeling

Regression modeling

Structural Equation modeling

Etc.

Usually called Multivariate or Multidimensional Statistics (try Google)

5. Statistical software – review

A. General statistical softwareCan prepare data (enter data, labels, clean data, transform data) and also compute individual

statistical procedures. They include many statistical procedures so these can be used nearly every time.

List of the most common:

SPSS (Statistical Package for Social Sciences) Origin. USA13 modules more information see http://www.spss.com/ or http://www.acrea.cz/Current version : 20Price : approx. 10 th USD for the full systemTrial version: for 15 days

SAS (Statistical analysis system)Origin. USAMore info: http://www.sas.com/offices/europe/czech/index/index.htmlagain individual modules Current version: 10Price: approx. 50 th USDTrial version: NO

5. Statistical software – review

List of the most common (continue):

STATISTICAOrigin. USAMore info: http://www.statsoft.cz/page/index.php again individual modules Current version: 8Trial version: for 30 daysPrice: approx. 5 th USDStatsoft Textbook: see(http://www.statsoft.cz/page/index2.php?pg=navigace&nav=31).

STATAOrigin. USAMore info: http://www.stata.com/capabilities/statisticalcap.htmlagain individual modules Current version: 10Trial version: NOPrice: approx. 3 th USD

5. Statistical software – review

List of the most common (continue):

R (R project)FREEWARE OPENSOURCE SOFTWAREDownload: http://www.r-project.org/. Current version: 2.7.Disadvantages: No menu, worse graphical abilitiesAdvantages: the most up-to-date to new statistical procedures, very low requirements for

hardware, many forums about software

5. Statistical software – review

B) Special statistical software

Can be used for specialized (advanced statistical procedures). Usually it is necessary to prepare data in some general statistical software (see above)

Examples:

AMOS – software for Structural Equation ModelingHLM – software for Multilevel ModelinglEM – software for Latent Vlase Analysis

etc. there are hundreds of these softwares, some of them are freeware, some are commercial softwares (ususally not very cheap one)

6. Data archives in Social sciences

Store data from quantitative surveys (sometimes also from qualitative ones)

- Usually national archives- There are many archive associations

What can be reached via data archives?

- Original Data – in many formats .for SPSS, SAS, Excel etc.

- Original Questionnaire

- Codebook – information about individual variables, their values and their labels (sometimes also frequency tables for all variables included in the data file)

6. Data archives in Social sciences - Additional services

• Possibility to find data for individual topic

• Possibility to find the list of books and articles based on selected data file

• Possibility to compute basic statistics without reaching a data (frequencies, crosstabulations, correlations)

• etc.

• Note: Some operations are free for some operations is necessary to register or pay

6. Data archives in Social sciences

Example:

Czech data archive (http://archiv.soc.cas.cz)

Use system NESSTAR

Other archives and its associations – see LINKS

Thanks for your attention

soukup@fsv.cuni.cz