SPSS Powerclass- Learn SPSS from Advanced to Ultimate

SPSS Powerclass: Learn SPSS from Advanced to Ultimate, available at $54.99, has an average rating of 4.3, with 90 lectures, based on 32 reviews, and has 2392 subscribers.

You will learn about Advanced data import methods in SPSS How to work with SPSS?in Workbook and Syntax mode? Advanced Descriptive Statistics in SPSS Ratio Statistics in SPSS TURF?Analysis in SPSS Survival Analysis Meta-Analysis Advanced-Data Visualization in SPSS And many more advanced SPSS topics! This course is ideal for individuals who are Researchers and Ph.D. Students or Social Scientists and Academicians or Data Analysis Professionals or Statistics and Data Science Professionals It is particularly useful for Researchers and Ph.D. Students or Social Scientists and Academicians or Data Analysis Professionals or Statistics and Data Science Professionals.

Enroll now: SPSS Powerclass: Learn SPSS from Advanced to Ultimate

Summary

Title: SPSS Powerclass: Learn SPSS from Advanced to Ultimate

Price: $54.99

Average Rating: 4.3

Number of Lectures: 90

Number of Published Lectures: 88

Number of Curriculum Items: 90

Number of Published Curriculum Objects: 88

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Advanced data import methods in SPSS

How to work with SPSS?in Workbook and Syntax mode?

Advanced Descriptive Statistics in SPSS

Ratio Statistics in SPSS

TURF?Analysis in SPSS

Survival Analysis

Meta-Analysis

Advanced-Data Visualization in SPSS

And many more advanced SPSS topics!

Who Should Attend

Researchers and Ph.D. Students

Social Scientists and Academicians

Data Analysis Professionals

Statistics and Data Science Professionals

Target Audiences

Researchers and Ph.D. Students

Social Scientists and Academicians

Data Analysis Professionals

Statistics and Data Science Professionals

Hi there! Welcome to SPSS Powerclass!

SPSS Statistics is the most popular GUI-based software for doing data analysis and Research. It’s the most preferred software for academicians and research professionals. However, most of the users of SPSS remain confined to the basic features of SPSS and end up doing what everyone else is doing. That’s why you see most of the research articles report the most common statistical tests like correlation, regression, factor analysis, and some basic forms of group difference tests like ANOVA  and t-test. This devoids research to methodological diversity, and neither it appeals to a genuine pursuit of knowledge.

The purpose of the SPSS Powerclass is to take the knowledge of SPSS to the next level. This course offers in-depth coverage of advanced features of SPSS, like:

Advanced data import methods in SPSS

How to work with SPSS in Workbook mode?

Advanced Descriptive Statistics in SPSS

Ratio Statistics in SPSS

TURF Analysis in SPSS

Advanced-Data Visualization in SPSS

and many more!

Pedagogy:

Step-by-step coverage offering an explanation of all options of a test

Coverage of basics and underlying concepts in each test

Manual calculation of tests, wherever relevant offered

Probelm-based teaching, where each test is explained by taking practical problems

Easy to understand language. 

I am sure this course will help you in taking your SPSS skills to the next level!

Become a power user of SPSS!!

Join SPSS Powerclass today!! 

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 Cohens 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

Instructors

Scholarsight Learning
Courses in High Impact Research & Technology

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3 stars: 3 votes

4 stars: 8 votes

5 stars: 20 votes

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