Statistical Analysis Of Questionnaire Data Using Spss

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

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

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, 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 questionsImport and prepare data: learn best practices for labeling, cleaning, and managing raw dataValidate your questionnaire: explore construct validity using Exploratory Factor Analysis (EFA) and assess reliability with Cronbach’s AlphaPerform exploratory data analysis (EDA): summarize data using descriptive statistics, graphs, and plotsConduct core statistical tests and analyses: from Chi-square to Correlation, Regression, and ANOVA—explained in theory and applied in SPSSBy the end of the course, you will be able to:Prepare and clean questionnaire data like a proValidate scales and measure internal consistencyVisualize and interpret key relationships between variablesChoose and run the correct statistical tests in SPSSExport results and report them with confidenceIdeal for social science researchers, graduate students, and anyone working with questionnaire-based data. No prior SPSS experience is needed just a willingness to learn by doing! Please note that a valid SPSS licence is needed.

Overview

Section 1: Introduction

Lecture 1 Welcome to the course

Lecture 2 Introduction

Lecture 3 The Communication Audit study

Lecture 4 Questionnaire and dataset

Lecture 5 The research questions

Lecture 6 The data analysis cycle

Lecture 7 The statistical package

Section 2: Data preparation

Lecture 8 Data preparation content and introduction

Lecture 9 Raw data format

Lecture 10 Import raw data into the statistical package

Lecture 11 Labeling of the dataset

Lecture 12 Verification and cleaning of the data

Section 3: Questionnaire validation

Lecture 13 Questionnaire validation content and introduction

Lecture 14 Construct validation with Exploratory Factor Analysis: Theory

Lecture 15 Construct validation with Exploratory Factor analysis hands-on with SPSS

Lecture 16 Export results from SPSS

Lecture 17 Testing reliability of the constructs with the Cronbach Alpha: Theory

Lecture 18 Testing reliability of the constructs with the Cronbach Alpha hands-on with SPSS

Lecture 19 Calculating composite construct scores in SPSS

Section 4: Exploratory Data Analysis

Lecture 20 Exploratory data analysis content and introduction

Lecture 21 Calculating descriptive statistics with SPSS

Lecture 22 Drawing graphs for single variables in SPSS

Lecture 23 Box plot with SPSS: The relationship between continuous and categorical variable

Lecture 24 Scatter plot with SPSS: The relationship between two continuous variables

Lecture 25 Clustered Bar chart with SPSS: The relationship between two categorical variable

Lecture 26 Tables with SPSS

Section 5: Statistical analysis

Lecture 27 Statistical analysis content and introduction

Lecture 28 How to do a statistical analysis

Lecture 29 Choose the correct statistical technique

Lecture 30 Relationship between two categorical variables: Pearson Chi-Square test: Theory

Lecture 31 Relationship between two categorical variables: Pearson Chi-Square test in SPSS

Lecture 32 Relationship between two continuous variables: Correlation analysis Theory

Lecture 33 Relationship between two continuous variables: Correlation analysis SPSS

Lecture 34 Influence of one independent variable on a dependent variable: SLR Theory

Lecture 35 Influence of one independent variable on a dependent variable: SLR Theory

Lecture 36 Influence of multiple independent variables on a dependent variable: MLR Theory

Lecture 37 Influence of multiple independent variables on a dependent variable: MLR SPSS

Lecture 38 Comparing the means of groups with Analysis of Variance(ANOVA) Theory

Lecture 39 Comparing the means of groups with Analysis of Variance (ANOVA) in SPSS

Section 6: Next steps

Lecture 40 Thank you

Lecture 41 Congratulations! Here's what is next…

Lecture 42 More resources for you

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