Why Attend This Training Course?

The SPSS for Beginners (Statistical Package for Social Sciences) short course provides you with fundamental training in the use of the the Statistical Package for Social Sciences (SPSS) software widely used in statistical data analysis. During the course, you will learn basic functionalities of the SPSS software and progress to a number of higher-level techniques that can be specifically used in the social sciences environment. The course is presented through a combination of presentations and hands-on sessions to help you perform data entry and analysis to create accurate tables and graphs that can be used in the classroom.

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What Is The Training Course Methodology?

This training course methodology depends on enabling participants to interact and exchange experiences, explore their competencies and achieve their career aspirations, using forward-thinking training arts, such as theoretical lectures and/or open discussion to exchange opinions and experiences, scenarios, innovative thinking brainstorming. Participants will receive an agenda including training material as a reference, in addition to some extra notes and booklets. 

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Who Should Attend This Training Course?

This training course is designed for individuals with some familiarity with SPSS, such as opening SPSS and saving output, is desired, but it is not a requirement.

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What Are The Training Course Objectives?

• Introduction about the basic functionalities of SPSS and the use of data editor

• Ability to modifying data files

• Understand tools and techniques in data preparation

• Learn to choose the correct statistical tests and in running statistical analyses

• Ability to read constructing tables and graphs

• Master in interpreting the data and graphs

• Discuss more advance topics such as nonparametric techniques

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What Is The Training Course Curriculum?

Theoretical Aspects of Measurement: Introduction

• Deciding on a conceptual framework

• Constructing an assessment framework

• Item construction

Using Data Editor

• Entering numeric data

• Entering string data

• Defining data

Modifying Data Files

• Deleting and inserting a case

• Deleting and inserting a variable

• Sorting and splitting data files

• Selecting cases

• Computing new variables

Data Preparation

• Data errors

• Data transformation

Running Analysis

• Descriptive statistics

• Assessing normality

• Interpreting output generated by assessing normality

• Interpreting graphs

Using Graphs

• Histograms

• Bar graphs

• Scatterplots Boxplots

• Line graphs

Choosing the Right Procedure

• Different statistical techniques

• Questions that need to be addressed

Differences between Groups

• Independent sample t-test

• Paired sample t-test

• ANOVA: One-ways analysis of variance