Udemy限免:IBM MPS掌握:高级统计分析的初学者 | Udemy Coupon | Udemy优惠码 | Udemy免费课程

Free Udemy Course IBM SPSS Mastery: Beginner to Advanced Statistical Analysis
IBM MPS掌握程度:高级统计分析初学者,掌握SPSS并在一门综合课程中释放数据分析从初学者到高级的力量! | Udemy付费课程限时免费 | Udemy Coupon | Udemy优惠码 | Udemy免费课程


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.


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.

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