Learning Outcomes

Introduction to Statistics and SPSS

Summary Statistics

Graphical Representations

Data Management

Lesson Summary

This module outlines the concepts and terminologies in data analysis and interpretation. Learn about sampling, types of variables, scales of measurement, and more. We will introduce the SPSS user interface and summary statistics for categorical and numerical variables. We will also examine graphical representations for exploratory data analysis.

Test of Hypothesis

More on Test of Hypothesis

Analysis of Variance (ANOVA)

Non-Parametric Test

This module presents the concepts of statistical data management. Learn to transform data, recode variables, make random selections, and sort data in SPSS. We will discuss how to carry out tests of hypotheses and analysis of variance (ANOVA) in SPSS. We will also consider five types of non-parametric tests and their applications in data analysis.

Correlation and Regression Analysis

More on Correlation and Regression Analysis

Binary Logistic Regression

Ordinal Data

A Case Study

This module explores correlation and regression models. We discuss the strength of associations, the correlation coefficient, and their implementation in SPSS. We consider scatterplot matrices and regression models. We also examine the multivariate analysis of variance (MANOVA), ordinal data analysis, and case studies of data analytics with SPSS.

Diploma in Data Analysis Using SPSS - Assessment

Learn how to use SPSS software to filter, analyse, interpret and visualise data in this free online diploma course.

Diploma in Data Analysis Using SPSS

Data analysis focuses on cleaning unprocessed data, processing it and visualising it with various tools and techniques. SPSS (Statistical Package for the Social Sciences) aids basic and advanced data analyses by making it easier for you to manipulate data and transform the outcome into usable information. This course shows you how to use SPSS for summary data analysis, hypothesis testing, analysis of variance, correlation and regression models.

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