Qualitative Analysis in SPSS- Logistic Regression Full Study

Qualitative Analysis in SPSS: Logistic Regression Full Study, available at $54.99, has an average rating of 5, with 30 lectures, based on 2 reviews, and has 7 subscribers.

You will learn about Understanding Logistic Regression: Students will learn the fundamentals of logistic regression and how to apply it using SPSS. Qualitative Data Analysis Techniques: Learners will explore various methods for analyzing qualitative data. Analyzing Relationships Between Variables: The course will teach students how to examine and interpret the relationships between different variables-categories. Creating a Thesis Model: Students will be guided through the process of creating a model for their thesis. How to conduct the bachelor degree final project. This course is ideal for individuals who are Students and Academics or Beginner to Intermediate Statisticians or Lifelong Learners or Data Analysts and Researchers It is particularly useful for Students and Academics or Beginner to Intermediate Statisticians or Lifelong Learners or Data Analysts and Researchers.

Enroll now: Qualitative Analysis in SPSS: Logistic Regression Full Study

Summary

Title: Qualitative Analysis in SPSS: Logistic Regression Full Study

Price: $54.99

Average Rating: 5

Number of Lectures: 30

Number of Published Lectures: 30

Number of Curriculum Items: 30

Number of Published Curriculum Objects: 30

Original Price: RON99.99

Quality Status: approved

Status: Live

What You Will Learn

Understanding Logistic Regression: Students will learn the fundamentals of logistic regression and how to apply it using SPSS.

Qualitative Data Analysis Techniques: Learners will explore various methods for analyzing qualitative data.

Analyzing Relationships Between Variables: The course will teach students how to examine and interpret the relationships between different variables-categories.

Creating a Thesis Model: Students will be guided through the process of creating a model for their thesis. How to conduct the bachelor degree final project.

Who Should Attend

Students and Academics

Beginner to Intermediate Statisticians

Lifelong Learners

Data Analysts and Researchers

Target Audiences

Students and Academics

Beginner to Intermediate Statisticians

Lifelong Learners

Data Analysts and Researchers

Unlock the full potential of your bachelor’s research with our comprehensive course, “Qualitative Analysis in SPSS: Logistic Regression Full Study.” This course is meticulously designed to equip you with the essential skills and knowledge required to conduct in-depth qualitative data analysis using SPSS.

In this course, you will learn to:

Analyze Variables: Gain a thorough understanding of different types of variables and how to analyze them effectively.

Understand Correlations: Learn how to identify and interpret the relationships between variables, crucial for drawing meaningful conclusions from your data.

Master Logistic Regression: Delve into logistic regression analysis, a powerful statistical method for modeling the relationship between a dependent variable and one or more independent variables.

Dimension Reduction: Explore advanced techniques like Factorial Correspondence Analysis (FCA) and Multiple Correspondence Analysis (MCA) to simplify complex data sets and uncover hidden patterns.

By the end of this course, you will have a solid foundation in qualitative data analysis and be proficient in using SPSS to conduct sophisticated statistical analyses. Whether you are working on your bachelor’s thesis or preparing for future research projects, this course will provide you with the tools and confidence to excel. Join us and transform your data into impactful insights! Yuhu!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Overview of This Course. What We Will Cover?

Lecture 3: Resources

Chapter 2: Research Design: Outlining the Logical Framework for Analysis

Lecture 1: Basic Theory

Lecture 2: Explaining the Database

Lecture 3: Key Elements of a Statistical Study: From Design to Analysis

Lecture 4: Two Ways of Thinking

Chapter 3: Getting Started: Preparing the Database for Analysis

Lecture 1: Data Cleaning

Lecture 2: Creating A New Variable

Lecture 3: Excel to SPSS

Lecture 4: Labeling Variables

Lecture 5: From Numerical to Ordinal

Lecture 6: Recomandations Of Chi-Square

Chapter 4: Descriptive Analysis

Lecture 1: Theory of Descriptive Analysis

Lecture 2: Creating Different Charts in SPSS

Lecture 3: Descriptive Analysis – Numerical Methods

Lecture 4: Creating Different Charts in Microsoft Excel

Lecture 5: Creating a Dashboard in Microsoft Excel

Lecture 6: Creating a Dashboard in Power BI

Chapter 5: Correspondence Factor Analysis (CFA)

Lecture 1: What is Correspondence Factor Analysis (CFA)

Lecture 2: Factorial Correspondence Analysis

Chapter 6: Multiple Correspondence Analysis (MCA)

Lecture 1: Theory of Multiple Factor Correspondence

Lecture 2: Quick Fix for a Common Error in Multiple Correspondence Analysis (MCA)

Lecture 3: Recoding of The Variables

Lecture 4: Multiple Correspondence Analysis

Lecture 5: Merging Two Variables into One

Chapter 7: Logistic Regression: Binary Logistic

Lecture 1: Regression Techniques for Categorical Variables | Binary Logistic

Lecture 2: Practical Logistic

Lecture 3: Check for Multicoliniarity

Lecture 4: Performance of the Model

Instructors

Matei Catana
Instructor at Udemy

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5 stars: 2 votes

Frequently Asked Questions

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