Title of the Workshop

The tittle of the workshop is ‘Two Days Workshop on Statistics and Data Analysis in SPSS’.

Overview

This workshop is a fully-fledged practical workshop that use the IBM SPSS (Statistical Package for Social Science) software to analyse, summarize, and interpret collected data for carrying out research. The lessons help to review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, as well as how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Participants will gain an understanding of when and why to use various statistical techniques as well as how to apply them with confidence, interpret their output, and graphically display the results.

In completion a ‘Participation Certificate’ will be awarded IT Centre, Vavuniya Campus of the University of Jaffna.

Target Group

This workshop is designed for school leavers from GCE Ordinary Level as well as GCE Advanced Level, students who undertake research and preparing project report for their undergraduates OR postgraduates degree, business professionals, and workers from government and non-organisation.

Duration and Schedule

Two days workshop, 8 Hours on Saturday – 9am to 5pm, and 7 hours on Sunday – 9am to 4pm

Fee Per Participant

Rs 4750 for Students and Rs 5000 for workers/ staff

Medium of Instruction

This workshop is conducted in bilingual languages including English and Tamil. Participants can use both English and/or Tamil in the lecture discussions.

Method of Teaching and Learning

The workshop will be delivered in a combination of lectures, computer laboratory practical sessions, and group works.

Objectives of the workshop

The objective of the workshop is:

• To provide the knowledge on statistical analysis.
• To provide the practical skill in using the IBM SPSS Statistics software.
• To produce capable personnel to analyse, summarize and interpret collected data for carrying out research.

Learning outcomes

After completing this workshop, the participants should be able to:

• Examine individual variables
• Test hypotheses about individual variables
• Test the relationship between categorical variables
• Test on the difference between two group means
• Test on differences between more than two group means
• Test the relationship between scale variables
• Predict a scale variable: Regression
• Know Bayesian statistics
• Overview of multivariate procedures

Course Outline

1.     Basic concepts in statistics

1.1  Measurement levels, mean, median, and standard deviation.

2.     Introduction to statistical analysis

2.1  Identify the steps in the research process

2.2  Principles of statistical analysis

3.     Examine individual variables

3.1  Identify measurement levels

3.2  Chart individual variables

3.3  Summarize individual variables

3.4  Examine the normal distribution

3.5  Examine standardized scores

4.     Test hypotheses about individual variables

4.1  Identify population parameters and sample statistics

4.2  Examine the distribution of the sample mean

4.3  Determine the sample size

4.4  Test a hypothesis on the population mean

4.5  Construct a confidence interval for the population mean

4.6  Tests on a single variable: One-Sample T Test, Paired-Samples T Test, and Binomial Test

5.     Test the relationship between categorical variables

5.1  Chart the relationship between two categorical variables

5.2  Describe the relationship: Compare percentages in Crosstabs

5.3  Test the relationship: The Chi-Square test in Crosstabs

5.4  Assumptions of the Chi-Square test

5.5  Pairwise compare column proportions

5.6  Measure the strength of the association

6.     Test on the difference between two group means

6.1  Compare the Independent-Samples T Test to the Paired-Samples T Test

6.2  Chart the relationship between the group variable and scale variable

6.3  Describe the relationship: Compare group means

6.4  Test on the difference between two group means: Independent-Samples T Test

6.5  Assumptions of the Independent-Samples T Test

7.     Test on differences between more than two group means

7.1  Describe the relationship: Compare group means

7.2  Test the hypothesis of equal group means: One-Way ANOVA

7.3  Assumptions of One-Way ANOVA

7.4  Identify differences between group means: Post-hoc tests

8.     Test the relationship between scale variables

8.1  Chart the relationship between two scale variables

8.2  Describe the relationship: Correlation

8.3  Test on the correlation

8.4  Assumptions for testing on the correlation

8.4  Treatment of missing values

9.     Predict a scale variable: Regression

9.1  What is linear regression?

9.2  Explain unstandardized and standardized coefficients

9.3  Assess the fit of the model: R Square

9.4  Examine residuals

9.5  Include 0-1 independent variables

9.6  Include categorical independent variables

10.  Introduction to Bayesian statistics

10.1 Bayesian statistics versus classical test theory

10.2 Explain the Bayesian approach

10.3 Evaluate a null hypothesis: Bayes Factor

10.4 Bayesian procedures in IBM SPSS Statistics

11.  Overview of multivariate procedures

11.1 Overview of supervised models

11.2 Overview of models to create natural groupings