Training on Data Management and Statistical Analysis using SPSS

The researchers today not only need to develop skills in carrying out community based researches but also develop skills in analyzing and managing data acquired through the hectic process. The acquired data should be used during the life of project for the purpose of planning, reporting and monitoring of performance.

Proficiency with statistical software packages is indispensable today for serious research in the sciences. SPSS (Statistical Package for the Social Sciences) is one of the most widely available and powerful statistical software packages.

It covers a broad range of statistical procedures that allow researcher to summarize data (e.g., compute means and standard deviations), determine whether there are significant differences between groups (e.g., t-tests, analysis of variance), examine relationships among variables (e.g., correlation, multiple regression), and graph results (e.g., bar charts, line graphs).

The workshop focuses on basic uses of SPSS including descriptive and inferential analysis.

The workshop is a step by step approach for data analysis for summarizing and presenting data, estimation, confidence intervals, hypothesis testing, comparing groups, measuring associations, seeing relationships and predictive analysis.

The workshop will focus more on understanding of key concepts and less on formulas and calculations, which can be done on statistical software (SPSS).

Course Outline:

Introduction to Statistical Analysis

• Explain the basic steps of the research process
• Explain differences between populations and samples
• Explain differences between experimental and non-experimental research designs
• Explain differences between independent and dependent variables

Introduction to SPSS statistical software

• SPSS interface and features
• Key terminologies used in SPSS
• Views: Variable, Data views, Syntax editor
• Data file preparation
• Data entry into SPSS
• Data manipulation: merge files, spit files, sorting files, missing values

Basic Statistics using SPSS

• Descriptive statistics for numeric variables
• Frequency tables
• Distribution and relationship of variables
• Cross tabulations of categorical variables
• Stub and Banner Tables

Graphics using SPSS

• Introduction to graphs in SPSS
• Graph commands in SPSS
• Different types of Graphs in SPSS

Statistical Tests using SPSS

• One Sample T Test
• Independent Samples T Test
• Paired Samples T Test
• One-Way ANOVA

Statistical Associations in SPSS

• Chi-Square test
• Pearson's Correlation
• Spearman's Rank-Order Correlation
• Bivariate Plots and Correlations for Scale Variables

Predictive Models using SPSS

• Linear Regression
• Multiple Regression
• Logistic Regression
• Ordinal Regression