Data Analysis With Spss Using Menu Bar And Spss Syntax

From Data Entry and Data Analysis to Interpretation: A Beginner's Guide to SPSS | Application of SPSS Syntax file

What you'll learn

Beginners can easily learn data analysis in SPSS

Import data from external sources, such as Microsoft Excel.

Calculate and interpret descriptive statistics for both continuous and categorical variables.

Data analysis for a manuscript, report, or a Master's or Ph.D. thesis.

Requirements

No prior experience with SPSS or statistics is required

Access to the SPSS statistical software

A good mindset to have when learning SPSS

Description

Struggling with data analysis for your manuscript, report, or thesis? Feeling overwhelmed by statistical software? This course is your complete, beginner-friendly guide to mastering the fundamentals of data analysis using SPSS. We will take you on a practical journey from Data Entry and Data Analysis to Interpretation, empowering you to confidently manage your data and present your findings.This course skips the complex jargon and focuses on a step-by-step, hands-on approach. By the end, you won't just know how to click buttons—you'll understand what you're doing and why you're doing it.What you will learn in this course:Navigate the SPSS interface with confidence and ease.Enter and import your own data, and prepare it for analysis by defining variables and assigning labels.Clean and manage your data, including handling missing values and computing new variables.Run and interpret essential descriptive statistics such as frequencies, means, and standard deviations.Create compelling charts and graphs to visualize your data for reports and presentations.Perform and interpret key statistical tests like the independent-samples t-test and the chi-square test.Draw meaningful conclusions from your results and effectively communicate your findings.Who is this course for?New Researchers in public health, marketing, or social sciences who need to analyze data for their studies and projects.Master's or Ph.D. Students working on a thesis or dissertation who need to perform data analysis.Professionals in various fields (e.g., social sciences, education, business) who need to analyze data from surveys, reports, or studies.Are there any prerequisites?No prior experience with SPSS or statistics is required.Access to the SPSS statistical software.You should have your research question and data collected and ready for analysis.If you are a beginner looking to transform raw data into clear, compelling results for your academic or professional work, this is the course for you.

Overview

Section 1: Introduction to SPSS

Lecture 1 Getting Started with SPSS

Lecture 2 Creating a Database in SPSS

Lecture 3 Data Measurement in SPSS | Nominal, Ordinal, and Scale

Lecture 4 An Introduction to SPSS Syntax

Section 2: SPSS Data Management | Part 1 - Data Import from Excel, CSV, Stata, Labelling

Lecture 5 Import Data from Excel to SPSS

Lecture 6 How to Import Data from a CSV File into SPSS

Lecture 7 Import Data from Stata to SPSS (SPSS version>29)

Lecture 8 Define variable label in SPSS using syntax

Lecture 9 Define Value Labels for Categorical Variables in SPSS using Syntax

Section 3: SPSS Data Management | Part 2 - Variables keep, delete, arrange, Transformation

Lecture 10 Variable Reordering & Re-arranging: Organizing Your SPSS Dataset

Lecture 11 Sorting Cases: Organizing Your Dataset by Row in SPSS

Lecture 12 Deleting & Keeping Variables: Cleaning Your Dataset in SPSS

Lecture 13 Compute New Variable: Creating New Variables in SPSS

Lecture 14 Recode Variables: Simplifying and Grouping Data in SPSS (Menu & Syntax)

Lecture 15 Advanced Recoding: Using Logical Operators (IF statements) in SPSS

Lecture 16 Categorical to Categorical Transformation with Logical Operators in SPSS

Lecture 17 How to Create Dummy Variables in SPSS (Applicable for upper version)

Lecture 18 Dummy Variables: Creating Binary Variables with the COMPUTE Method

Section 4: Visualizing Your Data with Graphs

Lecture 19 Creating Histograms in SPSS (Menu & Syntax)

Lecture 20 Boxplots: Visualizing Data Distribution and Outliers in SPSS ?

Section 5: Descriptive Statistics in SPSS ?

Lecture 21 Frequency Tables: Analyzing Categorical Data in SPSS ?

Lecture 22 Mean, Standard Deviation, & Variance: Summarizing Continuous Data in SPSS ?

Lecture 23 Another option for calculating Mean, Standard Deviation

Lecture 24 Median & Quartiles: Measures of Position in SPSS ?

Lecture 25 Cross-Tabulation: Analyzing Relationships Between Categorical Variables ?

Lecture 26 Comparing Means by Group: Analyzing Continuous Data Across Categories in SPSS ?

Lecture 27 Creating Publication-Ready Tables: From SPSS Output to Report ?

Section 6: Inferential Statistics in SPSS ?

Lecture 28 T-Test: Comparing Means Between Two Groups in SPSS (Menu & Syntax) ?

Lecture 29 One-Way ANOVA: Comparing Means Among Multiple Groups in SPSS ?

Section 7: Regression Analysis in SPSS ?

Lecture 30 Correlation: Relationships Between Variables in SPSS ?

Lecture 31 Linear Regression: Predicting a Continuous Outcome in SPSS ?

Lecture 32 Linear Regression Diagnostics & Interpretation: Validating Your Model's Findings

Lecture 33 Simple Logistic Regression: Predicting a Binary Outcome in SPSS ✅

Lecture 34 Logistic Regression: Using Categorical Predictors in SPSS ?

Lecture 35 Sample Table for Logistic Regression Findings for a Manuscript/Report

Lecture 36 Creating a Table for Logistic Regression Findings for a Manuscript/Report ?

New Researchers in public health, marketing, or social sciences who need to analyze data for their studies and projects.,Master's or Ph.D. Students who are working on a thesis or dissertation and need to perform data analysis for their research.,Professionals in various fields such as social sciences, health sciences, education, or business who need to analyze data from surveys, reports, or studies for their work.