introduction to spss1 (1)

Introduction to SPSSIntroduction to SPSS

Rakesh MohindraRakesh MohindraDepartment of LawsDepartment of Laws

Panjab University, ChandigarhPanjab University, Chandigarh

Rakesh MohindraRakesh MohindraDepartment of LawsDepartment of Laws

Panjab University, ChandigarhPanjab University, Chandigarh

SPSS: An Introduction SPSS: An Introduction Originally it is an acronym of Statistical Package for the

Social Science, Initial released in 1968 by SPSS Inc., later it stands for Statistical Product and Service Solutions.

In 2009 it was re-branded as PASW (Predictive Analytics SoftWare). It is again basically a computer program used for statistical analysis, acquired by IBM.

One of the most popular statistical packages which can perform highly complex data manipulation and analysis with simple instructions

In addition to statistical analysis, data management (case selection, file reshaping, creating derived data) and data documentation (a metadata dictionary is stored in the datafile) are features of this software.

Introduction (contd)Introduction (contd)

SPSS works on Operating system like Windows, Linux / UNIX & Mac Platform Java and perform a wide variety of statistical procedures.

Data management and analysis can be handled very well with SPSS.

Using SPSS we can manipulate data, make graphs and perform statistical techniques varying from means to regression.

Management of data and filesManagement of data and files

SPSS can read different types of data files.

You can open not only SPSS files but also excel and other types of files like csv, txt. Etc.

You can create a new data set with SPSS.

You can also edit, delete and view the contents of your data file.

OverviewOverview Measurement Scales. Type of Variables, Levels of Measurement. Discrete and Continuous Variables. Introduction to SPSS. Entering and Labeling Variables, Values. Transformation of Variables. Descriptive and Inferential Statistics. Running an analysis- explore differences, t test, ANOVA. Creating charts/graphs. Edit Outputs. Moving Charts and Graphs into Word.

Scientific Method of ResearchScientific Method of Research

Statement of the Problem.

Formulate the null hypothesis.

Design the Study.

Collect the Data.

Interpret the Data.

Draw Conclusions.

Statement of the Problem.

Formulate the null hypothesis.

Design the Study.

Collect the Data.

Interpret the Data.

Draw Conclusions.

What is Data?What is Data?a collection of facts from which conclusions may

be drawn; "statistical data"It represent the qualitative or quantitative

attributes of a variable or set of variables.

• An attribute is a property or characteristic of an object Examples: Refund, Sector,

Income

Attribute is also known as variable, field, characteristic, or a feature.

A collection of attributes describe an object

• Object is also known as record, point, case, sample, entity, instance, or observation

Tid Refund Sector Taxable Income Cheat

1 Yes Govt 125K No

2 No Pvt 100K No

3 No Govt 70K No

4 Yes Govt 120K No

5 No Govt 95K Yes

6 No Pvt 60K No

7 Yes Govt 220K No

8 No Govt 85K Yes

9 No Pvt 75K No

10 No Pvt 90K Yes 10

Attributes

Objects

Qualitative (or Categorical) attributes represent distinct categories rather than numbers. Mathematical operations such as addition and subtraction do not make sense. Examples:

eye color, letter grade, IP address, zip code

Quantitative (or Numeric) attributes are numbers and can be treated as such. Examples:

weight, failures per hour, number of TVs, temperature

TYPES OF ATTRIBUTES:TYPES OF ATTRIBUTES:

Discrete

Qualitative vs. Quantitative

Types of VariablesTypes of Variables

You can select type of variableYou can select type of variable String or alphanumericString or alphanumeric NumericNumeric

You can also select format of variableYou can also select format of variable CategoricalCategorical OrdinalOrdinal IntervalInterval

Variables and ConstantsVariables and Constants

Variables : Vary from person to person or object to object.

Constants : Remain constant from person to person or object to object.

A study is conducted to determine if there are gender differences in fine motor skills among five year olds from middle class families.

What are the variables in the study?

What are the constants in the study?

A trait might be a constant or a variable is determined by the nature of the particular study.

ExampleExample

Gender, Fine motor skills

Age, Socio-economic status

Levels of MeasurementLevels of Measurement

NominalNominal

OrdinalOrdinal

ScaleScale• RatioRatio

• IntervalInterval

NominalNominalA Nominal variable is one that has two or more categories, but there is no intrinsic ordering to the categories. if the values can be assigned to a code. The Values are distinct , they can be counted like (1,2,3..) lie students in class, doctors in a hospital

Objects observed to be similar on some characteristic (e.g., college student) are assigned to the same class or category, while objects observed to be dissimilar on that characteristic are assigned to different classes or categories. (Example: Car types: Toyota, Honda, Volvo, BMW, Audi, etc.)

Mutually exclusive unordered categories

Examples Sex (male, female)Race/ethnicity (White, Black, Latino, Asian, American, etc.)

OrdinalOrdinalA set of data/ values which can be ranked or a rating scales. You can count and order but not measure, ordinal data. The ordinal level of measurement is not only based on observing objects as similar or dissimilar, but also on ordering those observations in terms of an underlying characteristics. (Example: Height in size place ranking)

Ordered CategoriesExamples

Injury – Mild, Moderate, SevereIncome – Low, Medium, High

Even though we can order these from lowest to highest, the spacing between the values may not be the same across the levels of the variables.

Scale: Interval or RatioScale: Interval or RatioAn interval variable is similar to an ordinal variable, except that the intervals between the values of the interval variable are equally spaced.

An ordinal level of measurement can be developed into a higher level of measurement. Numbers can be assigned in such a way that equal numerical differences along the scale correspond to equal increments in the underlying characteristic. Like Map on a Scale.

Interval Scale of measurement is where any two adjacent units of measurement is same but the zero point is arbitrary. If this is done so that the score 0 corresponds to having none of the property being measured, the level of measurement is Ratio. (Example: Distance from home to school) Otherwise, it is interval. (Example: Temperature Scale)

Why does it matterWhy does it matter?? Statistical computations and analyses assume Statistical computations and analyses assume

that the variables have specific levels of that the variables have specific levels of measurementmeasurement

Can you compute average of hair color?Can you compute average of hair color? Does it makes sense to Does it makes sense to compute the average of compute the average of

educational experience?educational experience? AAn average requires a variable to be an interval. n average requires a variable to be an interval.

Continuous Data

1. If there are many different discrete values, then discrete data is often treated as continuous.

2. If there are very few discrete values, then discrete data is often treated as ordinal.

3. Qualitative (categorical) attributes are always discrete

Discrete Data

Any value on the continuum is possible (even fractions or decimals)Examples: Height, WeightMany “discrete” variables are often treated as continuous.Examples: BP, Heart RateA variable is continuous if in any unit of measurement, whenever it can take on the values a and b, it can also theoretically take on all the values between a and b.Has real numbers as attribute values.Can compute as accurately as instruments allow.Continuous attributes are typically represented as floating-point variables.

Data AnalysisData Analysis

Data analysis embraces both the problem of finding an appropriate model, on the one hand, and model estimation and testing, on the other.

In this context normality assumption becomes important.

In social sciences, it is hard to find typical bell shaped normal distribution.

Discrete & Continuous VariablesDiscrete & Continuous VariablesA variable is discrete if the values it takes on are integers or can be in

some unit of measurement in which they are integers. Has only a finite or countably infinite set of values Examples: zip codes, counts, or the set of religion type in a class. Often represented as integer variables

Qualitative (categorical) attributes are always discrete

A variable is continuous if in any unit of measurement, whenever it can take on the values a and b, it can also theoretically take on all the values between a and b.

Has real numbers as attribute values Can compute as accurately as instruments allow Examples: temperature, height, or weight Continuous attributes are typically represented as floating-point variables Quantitative (numeric) attributes can be either discrete or continuous.

Residence: 1 = College dormitory, 2 = Off campus apartment, 3 = Parents’ home, 4 = Other

Whether or not the student’s parents live in the same state as the student’s college

Class rank

Year graduated high school

Number of earned credits to date

Height

Family Income

Number of siblings

ExamplesExamples

Continuous

Discrete

Discrete

Discrete

Discrete

Discrete

Discrete

Discrete

How to Work on SPSSHow to Work on SPSS

Concepts (stats and scales).

Data entry (the workspace and Labels).

By hand

Import from Excel data file.

Creating, Computing and Transforming the Variables

Running an analysis- frequencies & Central tendency.

Graphical Representation.

Exporting Output.

Types of StatisticsTypes of Statistics

Descriptive- summarize or describe our Descriptive- summarize or describe our observations (frequencies)observations (frequencies)

Inferential- use observations to allow us to Inferential- use observations to allow us to make predictions (inferences) about a make predictions (inferences) about a situation that has not yet occurredsituation that has not yet occurred

Opening SPSSOpening SPSS The default window will have the data editor There are two sheets in the window:

1. Data view 2. Variable view

Data View windowData View window

The Data View window

This sheet is visible when you first open the Data Editor and this sheet contains the data

Click on the tab labeled Variable View

Click

Variable View windowVariable View window

This sheet contains information about the data set that is stored

with the dataset Name

The first character of the variable name must be alphabetic Variable names must be unique, and have to be less than 64

characters. Spaces are NOT allowed.

Variable View window: TypeVariable View window: Type

Type Click on the ‘type’ box. The two basic types of variables that you

will use are numeric and string. This column enables you to specify the type of variable.

Variable View window: WidthVariable View window: Width

Width Width allows you to determine the number of

characters SPSS will allow to be entered for the variable

Variable View window: DecimalsVariable View window: Decimals Decimals

Number of decimals It has to be less than or equal to 16

L3.14159265

Variable View window: LabelVariable View window: Label

Label You can specify the details of the variable You can write characters with spaces up to 256

characters

Defining the value labelsDefining the value labels

Click the cell in the values column as shown below For the value, and the label, you can put up to 60 characters. After defining the values click add and then click OK.

Click

Practice 1Practice 1

How would you put the following information into SPSS?

Value = 1 represents Male and Value = 2 represents Female

Name Gender HeightJAUNITA 2 5.4SALLY 2 5.3DONNA 2 5.6SABRINA 2 5.7JOHN 1 5.7MARK 1 6ERIC 1 6.4BRUCE 1 5.9

Practice 1 (Solution Sample)Practice 1 (Solution Sample)

Click

Saving the dataSaving the data

To save the data file you created simply click ‘file’ and click ‘save as.’ You can save the file in different forms by clicking “Save as type.”

Click

Sorting the Data

Click ‘Data’ and then click Sort Cases

Sorting the data (cont’d) Double Click ‘Name of the students.’ Then click

ok.

Click

Click

Practice 2 How would you sort the data by the ‘Height’ of

students in descending order? Answer

Click data, sort cases, double click ‘height of students,’ click ‘descending,’ and finally click ok.

Transforming dataTransforming data

Click ‘Transform’ and then click ‘Compute Variable…’

Transforming data (cont’d)Transforming data (cont’d)

Example: Adding a new variable named ‘lnheight’ which is the natural log of height

Type in lnheight in the ‘Target Variable’ box. Then type in ‘ln(height)’ in the ‘Numeric Expression’ box. Click OK

Click

Transforming data (cont’d)Transforming data (cont’d)

A new variable ‘lnheight’ is added to the table

Practice 3Practice 3 Create a new variable named “sqrtheight”

which is the square root of height. Answer

Types of VariablesTypes of VariablesWhat are variables you would consider in buying What are variables you would consider in buying

a second hand bike?a second hand bike?

Brand (Hero, Atlas)Brand (Hero, Atlas) Type of Bike (Road, Mountain, Racer)Type of Bike (Road, Mountain, Racer) Components (Shimano, High Grade)Components (Shimano, High Grade) How OldHow Old Condition (Excellent, good, Poor)Condition (Excellent, good, Poor) PricePrice Bike SizeBike Size Number of gearsNumber of gears

The basic AnalysisThe basic Analysis

The basic analysis of SPSS that will The basic analysis of SPSS that will be introduced in this class be introduced in this class

Frequencies This analysis produces frequency tables showing

frequency counts and percentages of the values of individual variables.

Descriptives This analysis shows the maximum, minimum,

mean, and standard deviation of the variables

Linear regression analysis Linear Regression estimates the coefficients of

the linear equation

Opening the sample dataOpening the sample data

Open ‘Employee data.sav’ from the SPSS Go to “File,” “Open,” and Click Data

Opening the sample dataOpening the sample data

Go to Program Files,” “SPSSInc,” “SPSS16,” and “Samples” folder.

Open “Employee Data.sav” file

FrequenciesFrequencies Click ‘Analyze,’ ‘Descriptive statistics,’ then

click ‘Frequencies’

FrequenciesFrequencies

Click gender and put it into the variable box. Click ‘Charts.’ Then click ‘Bar charts’ and click ‘Continue.’

Click Click

FrequenciesFrequencies

Finally Click OK in the Frequencies box.

Click

Using the Syntax editorUsing the Syntax editor Click ‘Analyze,’ ‘Descriptive statistics,’ then

click ‘Frequencies.’ Put ‘Gender’ in the Variable(s) box. Then click ‘Charts,’ ‘Bar charts,’ and click

‘Continue.’ Click ‘Paste.’

Click

Using the Syntax editorUsing the Syntax editor

Highlight the commands in the Syntax editor and then click the run icon.

You can do the same thing by right clicking the highlighted area and then by clicking ‘Run Current’

ClickRight Click!

Practice 4Practice 4

Do a frequency analysis on the Do a frequency analysis on the variable “minority”variable “minority”

Create pie charts for itCreate pie charts for it

Do the same analysis using the Do the same analysis using the syntax editorsyntax editor

AnswerAnswer

Click

DescriptivesDescriptives Click ‘Analyze,’ ‘Descriptive statistics,’ then Click ‘Analyze,’ ‘Descriptive statistics,’ then

click ‘Descriptives…’click ‘Descriptives…’ Click ‘Educational level’ and ‘Beginning Click ‘Educational level’ and ‘Beginning

Salary,’ and put it into the variable box.Salary,’ and put it into the variable box. Click OptionsClick Options

Click

DescriptivesDescriptives The options allows you to analyze other The options allows you to analyze other

descriptive statistics besides the mean and Std.descriptive statistics besides the mean and Std. Click ‘variance’ and ‘kurtosis’Click ‘variance’ and ‘kurtosis’ Finally click ‘Continue’Finally click ‘Continue’

Click

Click

Descriptive StatisticsDescriptive Statistics Finally Click OK in the Descriptives box. You will

be able to see the result of the analysis.

Regression AnalysisRegression Analysis

Click ‘Analyze,’ ‘Regression,’ then click ‘Linear’ from the main menu.

Regression AnalysisRegression Analysis

For example let’s analyze the model Put ‘Beginning Salary’ as Dependent and ‘Educational Level’ as

Independent.

εββ ++= edusalbegin 10

ClickClick

Regression AnalysisRegression Analysis Clicking OK gives the result

Plotting the regression linePlotting the regression line Click ‘Graphs,’ ‘Legacy Dialogs,’

‘Interactive,’ and ‘Scatterplot’ from the main menu.

Plotting the regression linePlotting the regression line Drag ‘Current Salary’ into the vertical axis box

and ‘Beginning Salary’ in the horizontal axis box. Click ‘Fit’ bar. Make sure the Method is

regression in the Fit box. Then click ‘OK’.

ClickSet this to Regression!

Practice 5Practice 5 Find out whether or not the previous

experience of workers has any affect on their beginning salary? Take the variable “salbegin,” and

“prevexp” as dependent and independent variables respectively.

Plot the regression line for the above analysis using the “scatter plot” menu.

AnswerAnswer

Click

Click on the “fit” tab to make sure the method is regression

Data Entry (import from Excel)

SPSS- Tutorial- Sample Files

Data Entry (import from Excel)16. Select the worksheet, the range (if desired), and if to read variable names- click OK

The data and variable names will appear

Running Analyses17. With SPSS open, select file- Open- Data

Running Analyses (Frequency)19. Select Analyze- Descriptive Stats- Frequencies

20. Select the desired variables and click the arrow to move them to the right side

Running Analyses (Frequency)

Running Analyses (Frequency)Result Tables and Graphs will appear

Running Analyses (Central Tendency)

Results will appear

27. Select some measures of central tendency and dispersion- click Continue then OK

Find differences between groupsFind differences between groups1. Click Analyze- Descriptive Stats- Explore

2. Move a scale variable to dependent, move the category variable to factor- click Statistics

Find differences between groupsFind differences between groups3. Select Descriptors- click continue- click Plots

4. Select the following- click Continue

Find differences between groupsFind differences between groups5. Click OK

The results will appear

Running Analyses (t- test)Running Analyses (t- test)

6. Click Analyze- Compare Means- Independent Samples t test

7. Select the test variable and the grouping variable, then click Define Groups


9. Select OK

8. Label the groups (in this case f or m)


The results will appear

Running Analyses (ANOVA)Running Analyses (ANOVA)10. Click Analyze- Compare Means-

One-Way ANOVA

11. Move the Numerical variable to the dependent list and move the categorical variable to the Factor list

Running Analyses (ANOVA)Running Analyses (ANOVA)

12. Click Options

13. Select Descriptive then Continue- then select PostHoc…

Running Analyses (ANOVA)Running Analyses (ANOVA)

14. Select Tukey then Continue

15. Click OK

Running Analyses (ANOVA)Running Analyses (ANOVA) Results will appear

The stars tell you where the significant differences occur

Creating ChartsCreating Charts

17. Move the variables to the right side and then click Charts

16. Click Descriptive Stats- Frequencies

The simplest way to make a chart is to create it as you are running an analysis (not always possible)


19. Click OK

18. Select the appropriate options and then click continue


20. Double click the chart to open the chart editor

The chart will appear in the

output window

Creating ChartsCreating ChartsYou get edit options by double clicking on an item. The changes are automatically added to the output

page once you close the chart editor

Table EditTable Edit21. Right click on any table- select SPSS Pivot Table Object- Open

22. In the Pivot table window, click Table looks

Export Charts and Graphs to WordExport Charts and Graphs to Word

The steps for charts and graphs are the same.

30. Right click on the chart and select copy.

31. In the correct location in the Word document, right click and select paste.

Export Charts and Graphs to WordExport Charts and Graphs to Word

The chart will appear in an editable format in the document.

Export Charts and Graphs to WordExport Charts and Graphs to Word32. To edit a pasted graph, right click the graph and click Edit Picture.

ResourcesResources Indiana University- Getting Started (useful instructions with screenshots)Indiana University- Getting Started (useful instructions with screenshots)

http://http://www.indiana.edu/~statmath/stat/spss/winwww.indiana.edu/~statmath/stat/spss/win//

UCLA- SPSS 12.0UCLA- SPSS 12.0 Starter Kit (useful movies, FAQs, etc) Starter Kit (useful movies, FAQs, etc) http://http://www.ats.ucla.edu/stat/spss/sk/default.htmwww.ats.ucla.edu/stat/spss/sk/default.htm

Texas A & M- a huge selection of helpful movies Texas A & M- a huge selection of helpful movies http://http://www.stat.tamu.edu/spss.phpwww.stat.tamu.edu/spss.php

University of Toronto- A Brief Tutorial (screenshots, instructions and basic University of Toronto- A Brief Tutorial (screenshots, instructions and basic stats)stats)http://www.psych.utoronto.ca/courses/c1/spss/page1.htmhttp://www.psych.utoronto.ca/courses/c1/spss/page1.htm

SPSS Statistics Coach and Tutorial (under Help) as well as the ZU librarySPSS Statistics Coach and Tutorial (under Help) as well as the ZU library

Online Statistics TextbookOnline Statistics Textbookhttp://http://www.statsoft.com/textbook/stathome.htmlwww.statsoft.com/textbook/stathome.html

For further Questions:[email protected]

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