Published 3/2025
Created by Habibur Rahman
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 81 Lectures ( 9h 3m ) | Size: 3.38 GB
Quickly get started with data analysis using SPSS for theses, dissertations, lab reports, research projects, and more.
What you’ll learn
Understand the Basic Statistical Concepts
Use SPSS to Enter, Manipulate and Clean a Dataset
Analyze Survey and Experimental Data
Answer Research Questions Using Appropriate Statistical Analyses
Present Results in APA Style
Requirements
Access to SPSS software
Description
Data analysis is an integral part of academic research. It is important to ensure that you are conducting the right analysis in the right way. However, as a beginner, it can feel overwhelming to know where to start or how to conduct an analysis and present the findings.This course is designed to equip you with essential data analysis skills so that you can carry out analysis independently. If you are taking a statistics course, this will serve as a supplement to your class, helping you complete homework and assignments with ease. For those working on a thesis, dissertation, or research project, the course will walk you through the entire analytical process—from data cleaning to reporting results—helping you produce high-quality, reliable, and valid findings.What You Will Learn:Statistics is a vast field with countless analyses and methods. However, this course focuses on the analyses you’re most likely to need in your academic work. I’ve carefully selected techniques that undergraduate students, graduate students, and researchers commonly use.The course begins with basic statistical concepts to help you better understand the subsequent materials. You’ll then learn how to work with SPSS, including data management and manipulation techniques. As you progress, you’ll move into preliminary analysis before exploring three core areas of statistical testing:Exploring Relationships – Learn techniques like correlation and regression to understand the relationships between variables.Comparing Groups – Explore methods such as ANOVA and t-tests to investigate differences between groups or conditions.Non-Parametric Tests – Learn how to analyze data that doesn’t meet the assumptions required for parametric analysis.Some Features of the Course:Coverage of the most commonly used analysesClearly organized sections on different topicsGuidance on selecting appropriate statistical testsConcepts explained in simple, easy-to-understand languagePractical demonstrations with realistic datasets and scenariosGuidance on presenting results in APA Style (templates included)Recommendations for additional resources for further learningBy the end of this course, you’ll have a solid understanding of data analysis and feel more confident in handling your research project. Start learning today and see how straightforward it can be!
Password/解压密码www.tbtos.com