Statistical Analysis of questionnaire data using SPSS

Name: Statistical Analysis of questionnaire data using SPSS
Rating: 5.0 (6 reviews)

Essential SPSS skills tailored for researchers and analysts: Learn the theory and apply it using real questionnaire data

Created byHennie Gerber

Last updated 7/2025

English

What you'll learn

Prepare and import questionnaire data into a statistical package by labeling variables, verifying accuracy, and cleaning data to ensure it is ready for analysis
Validate a questionnaire by conducting Exploratory Factor Analysis and the Cronbach Alpha coëfficent in SPSS
Explore data using SPSS by calculating descriptive statistics, creating graphs and tables, and visualizing relationships between variables with plots and charts
Conduct statistical analyses in SPSS by selecting appropriate techniques to test relationships between variables and compare group s

Course content

6 sections • 42 lectures • 5h 28m total length

Welcome to the course1:37
Introduction0:52
The Communication Audit study2:46
Discussion of the ABC company and communication audit study that will be used in all the practical analyses.
Questionnaire and dataset5:59
The research questions2:40
Discussion of the research questions that will be answered in the course
The data analysis cycle3:03
Discussion of the data analysis cycle that will be used for analysing questionnaire data
The statistical package5:21
Discussion of the statistical package SPSS that will be used in the course.

Data preparation content and introduction1:26
Introduction to the data preparation section
Raw data format3:45
Discussion of the raw data format, for example an Excel file that is a dataset
Import raw data into the statistical package5:32
Importing the data from Excel format into the statistical package
Labeling of the dataset12:37
Providing variable and value labels as well as measurement type in the variable view in SPSS
Verification and cleaning of the data10:04
Verification and cleaning of the variables in the dataset according to the measurement type.

Questionnaire validation content and introduction1:59
Construct validation with Exploratory Factor Analysis: Theory16:43
Discussion of Exploratory Factor Analysis that will be used to test validity of constructs in the scale in the questionnaire. This would be the theory and practical application. Assumptions of the statistical techniques will be discussed.
Construct validation with Exploratory Factor analysis hands-on with SPSS27:01
Practical application of Exploratory Factor Analysis to test validity of constructs in the scale in the questionnaire. This will be done hands-on in SPSS.
Export results from SPSS6:08
Exporting results from the output window of SPSS to MS Word
Testing reliability of the constructs with the Cronbach Alpha: Theory7:51
Discussion of the Cronbach Alpha coëfficient that will be used to test reliability of the items(Likert scale statements) of constructs in the scale in the questionnaire. This would be the theory and practical application. Assumptions of the statistical technique will be discussed.
Testing reliability of the constructs with the Cronbach Alpha hands-on with SPSS12:12
Practical application of the Cronbach Alpha coëfficient that will be used to test reliability of the items(Likert scale statements) of constructs in the scale in the questionnaire. This would be done hands-on in SPSS
Calculating composite construct scores in SPSS6:52
Please use this SPSS dataset with labels that is verified and cleaned with composite scores going forward if you want to be sure the calculations is correct

Exploratory data analysis content and introduction4:02
Calculating descriptive statistics with SPSS7:24
Calculation of descriptive statistics in SPSS according to the variable type
Drawing graphs for single variables in SPSS9:57
Drawing graphs in SPSS according to the variable type.
Box plot with SPSS: The relationship between continuous and categorical variable6:08
Creating a Box Plot hands-on in SPSS to show the relationship between a categorical and continuous variable
Scatter plot with SPSS: The relationship between two continuous variables4:36
Creating a Scatter Plot hands-on in SPSS to show the relationship between two continuous variables
Clustered Bar chart with SPSS: The relationship between two categorical variable3:59
Creating a Clustered Bar Chart hands-on in SPSS to show the relationship between two categorical and variables
Tables with SPSS8:14
Using the custom tables function in SPSS to create various tables and formatting.

Statistical analysis content and introduction3:02
How to do a statistical analysis4:30
Discussion of an example of how to do a proper statistical analysis and adhering to various criteria such as testing assumptions etc.
Choose the correct statistical technique7:59
Discussion of various types of relationships and choosing the correct statistical technique for analysis
Relationship between two categorical variables: Pearson Chi-Square test: Theory5:54
Discussion of the Pearson Chi-square test for assessing the relationship between two categorical variables. This will be the theory and application
Relationship between two categorical variables: Pearson Chi-Square test in SPSS11:56
Application of the Pearson Chi-square test for assessing the relationship between two categorical variables. This will be done hands-on in SPSS using the example dataset and questionnaire. This will be done with all the analyses in the course.
Relationship between two continuous variables: Correlation analysis Theory6:20
Discussion of the Pearson correlation analysis for assessing the relationship between two continuous variables. This will be the theory and application
Relationship between two continuous variables: Correlation analysis SPSS12:16
Application of the Pearson correlation analysis for assessing the relationship between two continuous variables. This will be done hands-on in SPSS
Influence of one independent variable on a dependent variable: SLR Theory10:08
Discussion of a Simple Linear Regression(SLR) to test then influence of one variable on another variable. The independent variable will influence the independent variable(continuous). This will be the theory and application
Influence of one independent variable on a dependent variable: SLR Theory15:49
Practical application of a Simple Linear Regression(SLR) to test then influence of one variable on another variable. The independent variable will influence the independent variable(continuous). This will be done hands-on in SPSS
Influence of multiple independent variables on a dependent variable: MLR Theory18:31
Discussion of a Multiple Linear Regression(MLR) to test then influence of more than one variable on a continuous variable. The independent variables will influence the independent variable(continuous). This will be the theory and application
Influence of multiple independent variables on a dependent variable: MLR SPSS22:23
Practical application of a Multiple Linear Regression(MLR) to test then influence of more than one variable on a continuous variable. The independent variables will influence the independent variable(continuous). This will be done hands-on in SPSS. Please look at the errata file: the DW statistic will be 1.84 not 2.418 if you use the Excel dataset.
Comparing the means of groups with Analysis of Variance(ANOVA) Theory11:44
Discussion of Analysis of Variance(ANOVA) that is used to compare means of groups for significant differences. So the relationship will be between a categorical variable(groups) and a continuous variable(averages or means of the variable). This will be the theory and application
Comparing the means of groups with Analysis of Variance (ANOVA) in SPSS15:55
Practical application of Analysis of Variance(ANOVA) that is used to compare means of groups for significant differences. So the relationship will be between a categorical variable(groups) and a continuous variable(averages or means of the variable). This will be done hands-on in SPSS

Requirements

This course focus on data gathered by using a questionnaire although most analyses can be used for data obtained from other sources. Participants must have SPSS installed with a valid licence in order to be able to do the practical analyses.

Description

Unlock the full potential of your survey data with SPSS no prior experience required! This hands-on course is your complete guide to the statistical analysis of questionnaire data using SPSS. Whether you're a student, lecturer, researcher, or data analyst, you’ll gain the essential skills to clean, validate, and analyze real-world survey data confidently and accurately.

From understanding the research process to performing rigorous statistical tests, you’ll follow a structured, step-by-step path:

Get oriented with the Communication Audit case study, dataset, and research questions
Import and prepare data: learn best practices for labeling, cleaning, and managing raw data
Validate your questionnaire: explore construct validity using Exploratory Factor Analysis (EFA) and assess reliability with Cronbach’s Alpha
Perform exploratory data analysis (EDA): summarize data using descriptive statistics, graphs, and plots
Conduct core statistical tests and analyses: from Chi-square to Correlation, Regression, and ANOVA—explained in theory and applied in SPSS

By the end of the course, you will be able to:

Prepare and clean questionnaire data like a pro
Validate scales and measure internal consistency
Visualize and interpret key relationships between variables
Choose and run the correct statistical tests in SPSS
Export results and report them with confidence

Ideal for social science researchers, graduate students, and anyone working with questionnaire-based data especially for a Master's or PhD. No prior SPSS experience is needed just a willingness to learn by doing! Please note that a valid SPSS licence is needed.

Who this course is for:

Everyone embarking on quantitative research including lecturers, students as well as other quantitative researchers. No previous knowledge of SPSS is necessary.

Statistical Analysis of questionnaire data using SPSS

What you'll learn

Explore related topics

Course content

Introduction7 lectures • 22min

Data preparation5 lectures • 33min

Questionnaire validation7 lectures • 1hr 19min

Exploratory Data Analysis7 lectures • 44min

Statistical analysis13 lectures • 2hr 26min

Next steps3 lectures • 3min

Requirements

Description

Who this course is for: