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How to Learn Intermediate Statistics for Data Science As A Self Starter[ Day - 14 ]
Naresh Maddela
Data science & ML ll Top Data Science Voice ll 1M+ impressions on LinkedIn || Top 1% on @TopMate
Intermediate Stats
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12. Standard Normal Distribution
13. Z score
14. Probability Density Function
15. Cumulative distribution function
16. Hypothesis Testing
17. Many different plotting graphs
18. Kernel Density Estimation
19. Central Limit Theorem
20. Skewness of Data
Covariance
Pearson Correlation Coefficient
Spearman Rank Correlation Coefficient
Importance of Correlation
Hypothesis Testing
Null Hypothesis
Alternative Hypothesis
Understanding Hypothesis testing
(T-test,Chi square test, p values)
Hypothesis Testing in Statistics
Hypothesis testing is a fundamental concept in statistics used to make inferences or draw conclusions about a population based on sample data. It helps determine whether there is enough evidence to reject a null hypothesis (H?) in favor of an alternative hypothesis (H?).
Conclusion: There is sufficient evidence to reject the company’s claim that the average weight is 500 grams.