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IBM SPSS Mastery: Beginner to Advanced Statistical Analysis

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IBM SPSS Mastery: Beginner to Advanced Statistical Analysis, available at $54.99, has an average rating of 3.5, with 217 lectures, based on 4 reviews, and has 2025 subscribers.

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You will learn about The basics of SPSS, including understanding the GUI and key menus. How to use the Analyze, Data, and Transform menus effectively. Techniques for creating and interpreting descriptive statistics. The process of generating and analyzing scatter plots. How to conduct and interpret correlation analysis. Methods for performing linear and multiple regressions. The fundamentals of logistic and quadratic regression analysis. Advanced SPSS projects including case studies and practical applications. Utilizing SPSS Modeler for predictive analytics and data modeling. Implementing hypothesis testing and statistical analysis using SPSS. This course is ideal for individuals who are Students – Those studying statistics, data science, or related fields who want to gain proficiency in SPSS for their academic work. or Researchers – Professionals conducting research who need to analyze data using SPSS. or Data Analysts – Individuals working in data analysis roles who want to enhance their skills with SPSS. or Business Analysts – Professionals who need to interpret and analyze data to support business decisions. or Healthcare Professionals – Individuals in the medical or healthcare field who require data analysis skills for research or clinical studies. or Social Scientists – Researchers in sociology, psychology, or other social sciences who use statistical methods for their work. or Market Researchers – Those involved in market research and consumer behavior analysis. or Academicians – Educators and teachers who need to perform statistical analyses for their academic work. or Beginners – Anyone interested in learning SPSS from scratch with no prior experience. or Professionals Seeking Career Advancement – Individuals looking to add statistical analysis skills to their professional toolkit. It is particularly useful for Students – Those studying statistics, data science, or related fields who want to gain proficiency in SPSS for their academic work. or Researchers – Professionals conducting research who need to analyze data using SPSS. or Data Analysts – Individuals working in data analysis roles who want to enhance their skills with SPSS. or Business Analysts – Professionals who need to interpret and analyze data to support business decisions. or Healthcare Professionals – Individuals in the medical or healthcare field who require data analysis skills for research or clinical studies. or Social Scientists – Researchers in sociology, psychology, or other social sciences who use statistical methods for their work. or Market Researchers – Those involved in market research and consumer behavior analysis. or Academicians – Educators and teachers who need to perform statistical analyses for their academic work. or Beginners – Anyone interested in learning SPSS from scratch with no prior experience. or Professionals Seeking Career Advancement – Individuals looking to add statistical analysis skills to their professional toolkit.

Enroll now: IBM SPSS Mastery: Beginner to Advanced Statistical Analysis

Summary

Title: IBM SPSS Mastery: Beginner to Advanced Statistical Analysis

Price: $54.99

Average Rating: 3.5

Number of Lectures: 217

Number of Published Lectures: 217

Number of Curriculum Items: 217

Number of Published Curriculum Objects: 217

Original Price: $99.99

Quality Status: approved

Status: Live

What You Will Learn

  • The basics of SPSS, including understanding the GUI and key menus.
  • How to use the Analyze, Data, and Transform menus effectively.
  • Techniques for creating and interpreting descriptive statistics.
  • The process of generating and analyzing scatter plots.
  • How to conduct and interpret correlation analysis.
  • Methods for performing linear and multiple regressions.
  • The fundamentals of logistic and quadratic regression analysis.
  • Advanced SPSS projects including case studies and practical applications.
  • Utilizing SPSS Modeler for predictive analytics and data modeling.
  • Implementing hypothesis testing and statistical analysis using SPSS.

Who Should Attend

  • Students – Those studying statistics, data science, or related fields who want to gain proficiency in SPSS for their academic work.
  • Researchers – Professionals conducting research who need to analyze data using SPSS.
  • Data Analysts – Individuals working in data analysis roles who want to enhance their skills with SPSS.
  • Business Analysts – Professionals who need to interpret and analyze data to support business decisions.
  • Healthcare Professionals – Individuals in the medical or healthcare field who require data analysis skills for research or clinical studies.
  • Social Scientists – Researchers in sociology, psychology, or other social sciences who use statistical methods for their work.
  • Market Researchers – Those involved in market research and consumer behavior analysis.
  • Academicians – Educators and teachers who need to perform statistical analyses for their academic work.
  • Beginners – Anyone interested in learning SPSS from scratch with no prior experience.
  • Professionals Seeking Career Advancement – Individuals looking to add statistical analysis skills to their professional toolkit.

Target Audiences

  • Students – Those studying statistics, data science, or related fields who want to gain proficiency in SPSS for their academic work.
  • Researchers – Professionals conducting research who need to analyze data using SPSS.
  • Data Analysts – Individuals working in data analysis roles who want to enhance their skills with SPSS.
  • Business Analysts – Professionals who need to interpret and analyze data to support business decisions.
  • Healthcare Professionals – Individuals in the medical or healthcare field who require data analysis skills for research or clinical studies.
  • Social Scientists – Researchers in sociology, psychology, or other social sciences who use statistical methods for their work.
  • Market Researchers – Those involved in market research and consumer behavior analysis.
  • Academicians – Educators and teachers who need to perform statistical analyses for their academic work.
  • Beginners – Anyone interested in learning SPSS from scratch with no prior experience.
  • Professionals Seeking Career Advancement – Individuals looking to add statistical analysis skills to their professional toolkit.

Welcome to “IBM SPSS Mastery: Beginner to Advanced Statistical Analysis”! This comprehensive course is designed to take you from a novice to a proficient user of SPSS, a powerful tool for statistical analysis. Whether you’re a student, researcher, or professional, this course will equip you with the skills needed to analyze data effectively and draw meaningful insights. Starting with the basics, you’ll learn the essential features of SPSS, including its graphical user interface and fundamental menus. As you progress, you’ll delve into advanced statistical techniques, explore various real-world projects, and master complex data analysis methods. By the end of this course, you’ll be confident in using SPSS for a wide range of statistical applications, making data-driven decisions with ease.

Section 1: SPSS – Beginners

In this section, you’ll get an introduction to SPSS and its graphical user interface (GUI). We’ll start with an overview of the course and then dive into understanding the basic menus and functions of SPSS, including File, Edit, View, Analyze, Data, Transform, Graphs, Utilities, Help menus, and diagnostic tools. By the end of this section, you’ll be familiar with the essential components of SPSS and ready to start your data analysis journey.

Section 2: SPSS – Advanced

Building on the foundational knowledge, this section delves into advanced features of SPSS. We’ll cover descriptive statistics through various case studies, including market summaries and diabetes case studies. You will learn about correlation matrices, scatter plots, linear regressions, and multiple regressions with practical examples from different industries. Additionally, we’ll introduce logistic and quadratic regressions, preparing datasets, and interpreting outputs. By the end of this section, you will have a solid understanding of advanced statistical techniques using SPSS.

Section 3: Advanced SPSS Project: Impact of EMI on Home Loan

This project-based section focuses on the impact of Equated Monthly Installments (EMI) on home loans. You’ll learn how to linearly model the relationship between EMIs and home loans, interpret outputs, and analyze scatter plots. This hands-on approach helps in applying theoretical knowledge to real-world data, enhancing your analytical skills.

Section 4: Advanced SPSS Project: Impact of Total Turnover in Equity Market

In this section, we explore the impact of total turnover in the equity market through multiple regression analysis. You’ll estimate coefficients, interpret outputs, and analyze scatter plots. This project helps you understand the dynamics of financial markets and the application of SPSS in economic data analysis.

Section 5: Advanced SPSS Project: Impact of Trade Data in Equity Market

This section deals with the impact of trade data on the equity market. You’ll import datasets, generate estimation outputs, interpret them, and analyze scatter plots. By the end of this section, you’ll be proficient in handling complex financial datasets and drawing meaningful insights using SPSS.

Section 6: SPSS Advanced Projects

This section includes various advanced SPSS projects, providing comprehensive hands-on experience. You’ll learn to analyze and import datasets, generate descriptive statistics, scatter plots, pie charts, correlation matrices, and significance testing. The projects cover linear regression theory, interpretation of scatter plots, and estimating outputs, equipping you with practical knowledge for advanced statistical analysis.

Section 7: SPSS Modeler

In this section, you’ll learn about SPSS Modeler and its significance. We’ll cover user training, modeling nodes, statistics of nodes, banking data, graph boards, quarterly outputs, association, and segmentation modeling nodes, and exporting outputs. You’ll also explore advanced topics like neural networks and building streams, enhancing your data modeling skills.

Section 8: SPSS GUI and Applications

This section focuses on the practical implementation of SPSS. You’ll learn to import datasets in text and CSV formats, understand mean and standard deviation, and navigate software menus. By the end of this section, you’ll be adept at using SPSS for various statistical analyses and data operations.

Section 9: SPSS – Correlation Techniques

This section covers basic and advanced correlation techniques using SPSS. You’ll learn to interpret and implement correlation theories, generate scatter plots, and analyze datasets through practical examples. This knowledge is crucial for understanding relationships between variables in your data.

Section 10: Linear Regression & Supervised Learning with SPSS

In this section, you’ll delve into linear regression and supervised learning. You’ll learn to create attributes for variables, generate regression equations, and interpret outputs through various examples. This section is designed to give you a deep understanding of linear regression modeling and its applications.

Section 11: SPSS – Multiple Regression Modeling

This section introduces basic multiple regression modeling using SPSS. You’ll explore important output variables and work through multiple regression examples. By the end of this section, you’ll be proficient in handling complex regression models and interpreting their outputs.

Section 12: Logistic Regression & Supervised Learning using SPSS

In this section, you’ll learn about logistic regression concepts and their application using SPSS. We’ll cover IBM SPSS Statistics Data Editor, generating outputs, and interpreting them through various examples. This section prepares you for advanced logistic regression analysis and its practical implementation.

Section 13: SPSS – Multinomial Regression

This section introduces multinomial-polynomial regression. You’ll work through health study examples, generate output, interpret parameters, and understand dataset structures. This advanced topic enhances your ability to analyze categorical data using SPSS.

Section 14: SPSS GUI for Statistical Analysis

The final section focuses on using the SPSS GUI for statistical analysis. You’ll learn data entry, arranging columns, inputting Likert scales, analyzing mean, median, and mode, performing t-tests, correlation analysis, and various other statistical tests. This section ensures you can effectively use SPSS for comprehensive data analysis.

Conclusion

By completing this course, you’ll gain a thorough understanding of SPSS, from beginner to advanced levels. You’ll be equipped with the skills to perform complex statistical analyses, interpret results, and apply your knowledge to real-world datasets. This course is designed to make you proficient in SPSS, empowering you to excel in your academic and professional pursuits.

Course Curriculum

Chapter 1: SPSS – Beginners

Lecture 1: Introduction to Course

Lecture 2: GUI understanding and User Training

Lecture 3: Understanding File Edit View Menus

Lecture 4: Understanding File Edit View Menus Continued

Lecture 5: Understanding Analyze Menu

Lecture 6: Understanding Data and Transform Menus

Lecture 7: Understanding Graphs Utilities Menus

Lecture 8: Understanding Help Menu and Diagnostic Tool

Chapter 2: SPSS – Advanced

Lecture 1: Introduction to Course

Lecture 2: Descriptive – Market Case Study

Lecture 3: Descriptive – Graph – Market Summary

Lecture 4: Descriptive – Charts – Diabetes Case Study

Lecture 5: Introduction to Correlations

Lecture 6: Example – Market Summary

Lecture 7: Example – Market Summary Continued

Lecture 8: Example – Diabetes

Lecture 9: Correlations Matrix

Lecture 10: Tech Mahindra Output and Scatter Plots

Lecture 11: Tech Mahindra Output and Scatter Plots Continued

Lecture 12: More on Scatter Plots

Lecture 13: Introduction to Linear Regressions

Lecture 14: Example – LIC Outputs

Lecture 15: Example – LIC Interpretations and Scatter Plots

Lecture 16: Example – PI Ratio and Interest Change

Lecture 17: Introduction to Multiple Regressions

Lecture 18: Home Loan – Estimates

Lecture 19: Home Loan – Outputs

Lecture 20: Home Loan – Interpretations

Lecture 21: Home Loan – Scatter Plots Analysis

Lecture 22: Diabetes – Outputs

Lecture 23: Diabetes – Outputs Continued

Lecture 24: Diabetes Interpretation

Lecture 25: Diabetes – Scatter Plots

Lecture 26: Introduction to Logistic Regression

Lecture 27: Outputs and Estimates

Lecture 28: Interpretations

Lecture 29: Introduction to Quadratic Regressions

Lecture 30: Preparing Dataset Using SPSS

Lecture 31: Preparing Dataset Using MS Excel

Lecture 32: LIC Outputs and Interpretations

Lecture 33: Quadratic Regressions Scatter Plots

Chapter 3: Advanced SPSS Project: Impact of EMI on Home Loan

Lecture 1: Introduction to Project

Lecture 2: Home Loan – Line of it eqn and Outputs

Lecture 3: Home Loan – Interpretations and Outputs

Lecture 4: Home loan – Scatter Plots

Chapter 4: Advanced SPSS Project: Impact of Total Turnover in Equity Market

Lecture 1: Introduction to Project

Lecture 2: Coefficients Estimates and Outputs

Lecture 3: Coefficients Estimates and Outputs Continued

Lecture 4: Interpretations of Output

Lecture 5: Multiple Regression – Scatter Plot

Lecture 6: Multiple Regression – Scatter Plot Continued

Chapter 5: Advanced SPSS Project: Impact of Trade Data in Equity Market

Lecture 1: Introduction to Project

Lecture 2: Import of Dataset

Lecture 3: Estimation Outputs

Lecture 4: Interpretation of Outputs

Lecture 5: Scatter Plots

Chapter 6: SPSS Advanced Projects

Lecture 1: Course Contents

Lecture 2: Analyzing and Importing a Dataset

Lecture 3: Generating Descriptive

Lecture 4: Generating Scatter Plots and Interpretations of Outputs

Lecture 5: Pie-Charts Output

Lecture 6: Importing Dataset

Lecture 7: Generating Correlations Matrix

Lecture 8: Generating Estimates

Lecture 9: Testing for Significance

Lecture 10: Linear Regression Theory

Lecture 11: Interpretation of Scatter Plots

Lecture 12: Explaining Dataset

Lecture 13: Estimates Outputs

Lecture 14: Analyzing and Interpreting Estimates

Lecture 15: Generating Correlation Matrix

Lecture 16: Generating Multiple Scatter Plots

Chapter 7: SPSS Modeler

Lecture 1: Introduction Significance and user Training

Lecture 2: Encode Password Tool

Lecture 3: Modeling Nodes

Lecture 4: Statistics of Nodes

Lecture 5: Node Pallets

Lecture 6: Banking Data

Lecture 7: Examining the High Price

Lecture 8: Source Nodes and Importing Source Nodes

Lecture 9: Understanding the Graph Boards

Lecture 10: Statistic File

Lecture 11: Quarterly Outputs

Lecture 12: Association and Segmentation Modeling Nodes

Lecture 13: Understanding Export

Lecture 14: Output types of Means

Lecture 15: Pistachio Excel to Save Export Node

Lecture 16: Hierarchy Density Based Scan

Lecture 17: Streams

Lecture 18: Auto Recovery

Lecture 19: Stream Description and Running Streams

Lecture 20: Working with Data

Lecture 21: Housing Index Price Analysis

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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