Course Details

IBM SPSS Statistic is one of the most population Statistical software package in the world. Primarily used by social scientist but later adopted by other disciplines, especially medical and health scientists. This short course intends to cover some of the most popular usage of Statistics with real life data. Participants will be able to apply SPSS, analyse and interpret Statistics using SPSS.

The course will cover data entering, data labelling, data cleaning, variable computing, variable transforming, data file creating, and doing data analysis (mostly using menus) including summary statistics, hypothesis test, 95% CI, ANOVA, non-parametric method, RR, OR, correlation, linear regression, logistic regression, Cox’s regression and sample size calculation.

• Edit and creation of data file (entering, labelling, creating, cleaning, etc.)
• Introduction to most popular SPSS functions and tools. These functions and tools will help students to manipulate SPSS data files including open, create, transform, etc.,
• Creation of appropriate graphs and summary statistics using SPSS,
• Conduct appropriate hypothesis testing such as an independent samples t test or paired sample t-test or One-Way ANOVA to analyse symmetric numerical data,
• Conduct appropriate non-parametric tests such as Wilcoxon rank sum test, Wilcoxon signed rank test or Kruskal Walis test when numerical data is asymmetric,
• Predict the effect of exposures (numerical or categorical or a combination of both) on the outcome where outcome is continuous – using Simple and multiple linear regression.
• Predict the effect of exposures (numerical or categorical or a combination of both) on the outcome where outcome is categorical binary – using Simple and multiple logistic regression.
• Examine the association between an exposure and an outcome variable, where they are both binary or multinomial (more than two categories).
• Examine the effect of exposures on the outcome where outcome is categorical binary and time dependent (time to event data) or survival analysis.

This short course intends to deliver training on the application of SPSS. Participants should be able to do everything detailed in the course outline. Hence, basic Statistical knowledge such as classification of data, visualization of data using graphs and summary statistics, Independent sample t test, Paired sample t test, confidence interval, ANOVA test, non-parametric methods such as Wilcoxon rank sum test, Wilcoxon signed rank test, Kruskal Walis test, chi-square analysis, relative risk (RR), odds ratio (OR), Simple and multiple linear regression, logistic regression, Cox regression and sample selection are required.

All participants must bring a laptop (Mac or Windows) to this course which has either licenced SPSS or a trial version installed. You can choose to use your organizational version (most universities have site licence) or you can choose to purchase a student or grad version for less than $100.