About GNU PSPP

GNU PSPP is a program for statistical analysis of sampled data. It is a free as in freedom replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions. Benefit of PSPP is your copy of PSPP will not “expire”. Neither are there any artificial limits on the number of cases or variables which you can use. PSPP is a stable and reliable application. It can perform descriptive statistics, T-tests, anova, linear and logistic regression, measures of association, cluster analysis, reliability and factor analysis, non-parametric tests and more. Its backend is designed to perform its analyses as fast as possible, regardless of the size of the input data. You can use PSPP with its graphical interface or the more traditional syntax commands.

A brief list of some of the PSPP’s features follows below.

• No license fees.
• No expiration period.
• Support for over 1 billion cases.
• Support for over 1 billion variables.
• Syntax and data files which are compatible with those of SPSS.
• A choice of terminal or graphical user interface.
• Easy data import from spreadsheets, text files and database sources.
• Fast statistical procedures, even on very large data sets.
• A fully indexed user manual.
• PSPP is particularly aimed at statisticians, social scientists and students requiring fast convenient analysis of sampled data.

Course Outline for GNU PSPP

1. Introduction

1.1. Introduction to PSPP

1.2. PSPP history

2. Creating Data Files

2.1. Defining Variables

2.2. Datatype: String, Number, Date

2.3. Data entry

2.4. Saving your work

3. Starting with pspp

3.1. Getting your data in

3.2. Importing Data from a CSV File

3.3. Importing Data from a Excel File

3.4. Importing Data from a Text File

3.5. Reading data from other sources

3.6. Exporting

4. Combining Data Files

4.1. ADD FILES

4.2. MATCH FILES

4.3. UPDATE

5. Manipulating variables

5.1. ADD VARIABLES

5.2. DELETE VARIABLES

5.3. Add Cases

5.3. DELETE CASE

5.4. ADD VALUE LABELS

5.5. DISPLAY

5.6. FORMATS

5.7. LEAVE

5.8. MISSING VALUES

5.9. SORT VARIABLES

6. Data transformations

6.1. SORT CASES

6.2. COMPUTE

6.3. RECODE

6.4. COUNT

6.5. FLIP

6.7. IF

6.8. AGGREGATE

6.9. AUTORECODE

7. Selecting data for analysis

7.1. FILTER

7.2. N OF CASES

7.3. SAMPLE

7.4. SELECT IF

7.5. SPLIT FILE

8. Operators

8.1. Arithmetic Operators

8.2. Logical Operators

8.3. Relational Operators

9. Functions

9.1. Mathematical Functions

9.2. String Functions

9.3. Time & Date Functions

9.4. Statistical Functions

10. Descriptive Statistics

10.1. DESCRIPTIVES

• MEAN
• MEDIAN
• MODE

10.2. FREQUENCIES

10.3. GRAPH

• Scatterplot
• Histogram
• Bar Chart

11. Data Screening and Transformation

11.1. Identifying incorrect data

11.2. Dealing with suspicious data

11.3. Inverting negatively coded variables

11.4. Testing data consistency

11.5. Testing for normality

12. Statistically Test

12.1. CORRELATIONS

12.2. REGRESSION

12.3. Chisquare Test

12.4. CROSSTABS

12.5. T-TEST

• One Sample Mode
• Independent Samples Mode
• Paired Samples Mode

12.6. ANOVA

12.7. RELIABILITY