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Home » Ebooks & Tutorials » Technical » Development Training » Practical Data Analysis with SPSS | Udemy

Practical Data Analysis with SPSS | Udemy

08/05/2025 Tut4DL Leave a Comment


Practical Data Analysis with SPSS | Udemy
English | Size: 3.39 GB
Genre: eLearning

Unlock Data Insights with SPSS

What you’ll learn
Understand fundamental statistical concepts.
Install and navigate the SPSS interface, understanding its layout, menus, and key features.
Conduct inferential statistics including t-tests, ANOVA, correlation analysis, and chi-square tests.
Import datasets from Excel file, clean, organize, and transform data.
Perform descriptive statistics such as mean, median, standard deviation, and frequency distributions.
Generate clear and impactful charts and graphs.
Develop the ability to read and understand SPSS output.
Present results in standard academic format, adhering to APA style.

Master Data Analysis with Confidence

Starting with data analysis can feel complex, especially when working on a statistics assignment, research project, thesis, or handling business-related data. This course is structured to simplify the learning process, offering practical skills and clear explanations to help you approach analysis with confidence.

Why Take This Course?

Comprehensive Coverage – The course brings together key topics in one place, from basic statistical concepts to more advanced techniques.

Practical, Step-by-Step Approach – Concepts are explained in straightforward language, supported by demonstrations using real data.

Helpful Resources – Includes templates, APA-style reporting tips, and support to assist with common questions and challenges.

What You’ll Learn

The course is designed to build both understanding and practical ability in data analysis. Key learning areas include:

Foundations of Statistics – Clear explanations of core statistical concepts to help you start strong.

Working with SPSS – How to manage, manipulate, and analyze data using SPSS.

Data Preparation and Cleaning – Identify and correct issues like missing data, incorrect formats, or outliers to ensure your analysis is accurate.

Key Analytical Techniques:

Exploring Relationships – Use correlation and regression to understand how variables are connected.

Comparing Groups – Apply t-tests and ANOVA to examine group differences.

Non-Parametric Tests – Learn approaches for data that don’t meet the assumptions of standard statistical tests.

Don’t let data analysis hold you back. Enroll now and gain the skills you need to excel in your academic or professional journey!

Who this course is for:
University Students
Researchers
Business Professionals
Data Analysts

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Development Training Data Analysis, SPSS

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