SPSS Powerclass: Learn SPSS from Advanced to Ultimate

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Basic Data Entry

Lecture 1: Data Entry in SPSS Advantage Over Excel

Lecture 2: Understanding Name of Type of Variable

Lecture 3: Understanding Width and Decimals

Lecture 4: Understanding Labels

Lecture 5: Understanding values

Lecture 6: Understanding Missing Value

Lecture 7: Coulmns and Alignment

Lecture 8: Understanding Measures and Role

Chapter 3: Advanced Descriptive Statistics in SPSS

Lecture 1: Descriptive Analysis: Population Descriptives

Chapter 4: Ratio Statistics in SPSS

Lecture 1: Introduction and Usage

Lecture 2: What is Average Absolute Deviation (AAD)

Lecture 3: What is Coefficient of Dispersion (COD)

Lecture 4: What is Coefficient of Variation (COV)

Lecture 5: What is Price Related Bias

Lecture 6: What is Price Related Differential PRD

Lecture 7: Understanding Confidence Interval of PRD and Concentration Index

Lecture 8: Calculating Ratio Statistics in SPSS_Hypothesis Setting Data and Choosing Op

Lecture 9: Interpretation of Output of Ratio Statistics

Lecture 10: APA Style Write Up of Ratio Statistics

Chapter 5: TURF Analysis in SPSS

Lecture 1: What is TURF Analysis and When to Use It?

Lecture 2: Defining TURF Analysis

Lecture 3: What TURF Calculates?

Lecture 4: Who Discovered TURF Analysis?

Lecture 5: Assumptions of TURF Analysis?

Lecture 6: Applications of TURF Analysis

Lecture 7: Manual Calculation of TURF

Lecture 8: TURF Analysis in SPSS: Understanding Input Options

Lecture 9: Interpreting SPSS Output of TURF Analysis: Part 1

Lecture 10: Interpreting SPSS Output of TURF Analysis: Part 2

Lecture 11: APA Style Write Up of TURF Analysis

Chapter 6: Advanced data Visualization in SPSS

Lecture 1: Introduction to Advanced Data Visualization in SPSS

Lecture 2: What is Meaning of a Distribution?

Lecture 3: Understanding Statistical Distributions

Lecture 4: Creating Frequency and Probability Distributions in SPSS

Lecture 5: Understanding Fat Tail and Thin Tail Distributions

Lecture 6: Difference between FAT tail and THIN Tail Distributions

Lecture 7: PP Plots in SPSS

Lecture 8: Interpreting PP Plots in reference to the mid line

Lecture 9: What are QQ Plots

Lecture 10: Creating and Interpreting QQ Plots in SPSS

Lecture 11: How to Use QQ Plot to improve Normality of Your Variable

Lecture 12: Relationship Maps in SPSS

Chapter 7: Survival Analysis

Lecture 1: Introduction to Survival Analysis

Lecture 2: What is Survival Analysis?

Lecture 3: History of Survival Analysis

Lecture 4: Terminology: Time Event and Residual Life

Lecture 5: Terminology: Understanding Hazard, Hazard Rate and Survival Rate

Lecture 6: Terminology: Understanding Conditional Probability in Survival Analysis

Lecture 7: Terminology: Understanding Censored and Uncensored Data

Lecture 8: Terminology: Understanding Mean Time Between Failures vs. Mean Time To Failure

Lecture 9: Purpose of Survival Analysis

Lecture 10: Understanding Nature of Data Required to Run Survival Analysis

Lecture 11: Types of Survival Analysis

Lecture 12: When to Use Kaplan-Meier vs Cox Regression?

Lecture 13: Research Examples of Kaplan-Meier and Cox Regression Methods

Lecture 14: Setting Data for Survival Analysis

Lecture 15: Setting Objective and Hypothesis of Your SA Research

Lecture 16: Understanding Input Options of Kaplan Meier Method

Lecture 17: Interpreting Case Processing Summary and Survival Tables

Lecture 18: Interpreting Mean Survival Median and Percentiles

Lecture 19: Interpreting Pairwise Comparison

Lecture 20: Interpreting Survival Function Plot

Lecture 21: Interpreting Survival Function with other Statistical Results

Lecture 22: APA Style Report Writing of Kaplan Meier Survival Analysis

Lecture 23: Project in Survival Analysis: Replicating a Real Study

Lecture 24: References on Survival Analysis

Chapter 8: Meta Analysis

Lecture 1: Introduction to Meta Analysis

Lecture 2: What is Meta Analysis and Why You Should Know About It?

Lecture 3: Relationship Between Systematic Review and Meta Analysis

Lecture 4: Locating Meta Analysis in the Family of Other Research Techniques

Lecture 5: Is Meta-Analysis is Better than Hypothesis Testing?

Lecture 6: Outcome of Meta Analysis: Effect Size, Forest Plot, and Publication Bias

Lecture 7: Statistical Model of Meta-Analysis

Lecture 8: What is Effect Size?

Lecture 9: Understanding and Calculation of Cohen's d

Lecture 10: Downloading and Installing Meta Analysis Package in JAMOVI

Lecture 11: Types of Meta Analytic Techniques in Software Packages

Lecture 12: Aggregate Data (AD) vs. Individual Participant Data (IPD) Meta-Analysis

Lecture 13: Organizing Your Data for a Correlation Based Meta Analysis

Lecture 14: Meta Analysis in Jamovi- Part 1 Data Import and Input Options

Lecture 15: Understanding Model Estimators

Lecture 16: Understanding Fixed Effect Estimator and Its Formula

Lecture 17: Understanding Random Effect Model and When to Use Fixed Vs. Random Effect Model?

Lecture 18: How to Troubleshoot 'need finite xlim values' error in Jamovi?

Lecture 19: Understanding Maximum Likelihood and Restricted Maximum Likelihood Estimators

Lecture 20: Understanding DerSimonian-Laird Model Estimator

Lecture 21: Understanding and calculation of Hedges g estimator