Statistics for Data Science and Business Analysis
Statistics you need in the office: Descriptive & Inferential statistics, Hypothesis testing, Regression analysis
4.50 (47282 reviews)

219 454
students
5 hours
content
Feb 2024
last update
$119.99
regular price
What you will learn
Understand the fundamentals of statistics
Learn how to work with different types of data
How to plot different types of data
Calculate the measures of central tendency, asymmetry, and variability
Calculate correlation and covariance
Distinguish and work with different types of distributions
Estimate confidence intervals
Perform hypothesis testing
Make data driven decisions
Understand the mechanics of regression analysis
Carry out regression analysis
Use and understand dummy variables
Understand the concepts needed for data science even with Python and R!
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Comidoc Review
Our Verdict
The Statistics for Data Science and Business Analysis course on Udemy offers a strong foundation in essential statistical concepts while using engaging business examples. However, beginners may face difficulties with advanced topics and the insufficient practice materials. The course's reliance on Excel may also limit learners who wish to use alternative data analysis tools. While some students might appreciate the artificial instructor persona, others may find it distracting. Despite these minor issues, this course is an excellent starting point for those ready to dive into statistical concepts in a business context.
What We Liked
- Comprehensive coverage of various statistical topics such as descriptive & inferential statistics, hypothesis testing, and regression analysis
- Explains concepts in a straightforward and concise manner, making it accessible to learners without heavy statistical background
- Includes business-related examples that bring statistical concepts closer to real-life scenarios
- Well-structured course design with quizzes following lessons to reinforce understanding and retention
Potential Drawbacks
- Advanced topics might be challenging for absolute beginners due to minimal exercises and insufficient explanations
- Heavy reliance on Excel for examples, which could limit the applicability of learned concepts to other data analysis tools
- Artificial instructor persona and tone may impact overall learning experience for some learners
- Lacks supplementary materials like PowerPoint slides or PDFs, making note-taking challenging
Related Topics
1298780
udemy ID
20/07/2017
course created date
30/07/2019
course indexed date
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