Statistics for Business Analytics and Data Science A-Z™
Learn The Core Stats For A Data Science Career. Master Statistical Significance, Confidence Intervals And Much More!
4.51 (12490 reviews)
68 563
students
6 hours
content
Jan 2025
last update
$129.99
regular price
What you will learn
Understand what a Normal Distribution is
Understand standard deviations
Explain the difference between continuous and discrete variables
Understand what a sampling distribution is
Understand the Central Limit Theorem
Apply the Central Limit Theorem in practice
Apply Hypothesis Testing for Means
Apply Hypothesis Testing for Proportions
Use the Z-Score and Z-Tables
Use the t-Score and t-Tables
Understand the difference between a normal distribution and a t-distribution
Understand and apply statistical significance
Create confidence intervals
Understand the potential pitfalls of overusing p-Values
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Our Verdict
Statistics for Business Analytics and Data Science A-Z™ offers a solid foundation in essential statistical methods, catering specifically to those pursuing data science careers. While there are areas for improvement mainly related to explanation clarity and structure, the overall quality of instruction and focus on practical applications make it a worthwhile course to consider. Keep in mind that you might need additional resources to reinforce your learning.
What We Liked
- Comprehensive coverage of key statistical concepts relevant to business analytics and data science
- Engaging teaching style and clear explanations from an experienced instructor
- Strong emphasis on practical applications, helping learners understand the relevance of statistical methods
- Live examples and exercises that enhance understanding and reinforce learning
- User-friendly course structure, making complex topics easier to grasp
Potential Drawbacks
- Occasional unclear explanations requiring supplementary learning materials
- Lack of slide preparation and delivery professionalism in some instances
- Limited elaboration on certain concepts like hypothesis framing and null hypothesis rejection
- Incomplete or missing information necessitating external research to continue with the course
Related Topics
1175200
udemy ID
10/04/2017
course created date
30/07/2019
course indexed date
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