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Course Outline
Introduction
Getting Started with SPSS
- Introduction to SPSS interface and functionalities
- Importing and exporting data files
- Basic data entry and management
Obtaining, Editing, and Saving Statistical Output
- Generating statistical reports
- Customizing output tables and charts
- Saving and exporting analysis results
Manipulating Data
- Data transformation techniques
- Re-coding variables and computing new ones
- Managing missing data
Descriptive Statistics Procedures
- Calculating measures of central tendency and variability
- Frequency distributions and cross-tabulations
- Visualizing data with charts and graphs
Evaluating Score Distribution Assumptions
- Normality tests and graphical assessments
- Assessing skewness and kurtosis
- Checking for outliers
t-Tests
- Independent samples t-test
- Paired samples t-test
- Interpreting t-test results
Univariate Group Differences: ANOVA and ANCOVA
- One-way ANOVA and post-hoc comparisons
- Factorial ANOVA for multiple variables
- Introduction to ANCOVA and its applications
Multivariate Group Differences: MANOVA
- Understanding MANOVA concepts
- Running MANOVA tests in SPSS
- Interpreting MANOVA output
Nonparametric Procedures for Analyzing Frequency Data
- Chi-square tests of independence
- Mann-Whitney U test and Wilcoxon signed-rank test
- Kruskal-Wallis H test for non-parametric ANOVA
Correlations
- Pearson correlation coefficient
- Spearman rank correlation
- Partial and point-biserial correlation
Regression with Quantitative Variables
- Simple linear regression analysis
- Multiple regression models
- Interpreting regression coefficients and diagnostics
Regression with Categorical Variables
- Dummy variable coding for categorical data
- Logistic regression analysis
- Interpreting odds ratios and logistic model fit
Principal Components Analysis and Factor Analysis
- Exploratory factor analysis (EFA)
- Principal components analysis (PCA) techniques
- Factor rotation methods and interpretation of results
Summary and Next Steps
Requirements
- Basic understanding of mathematical concepts
- No prior experience with SPSS required
- Familiarity with basic statistics is beneficial but not mandatory
Audience
- Data analysts
- Researchers
- Business professionals working with statistical data
21 Hours
