A 7-day study plan from beginner to advanced level to learn 50+ concepts in statistics.

Basic Statistics: 2 Days

1. What is Statistics And What are types of statistics?
2. Introduction to probability
3. Addition rule for probability
4. Multiplication rule for probability
5. Descriptive And Inferential Statistics
6. Population and Sample
7. Measure Of Central Tendency (Mean, Median, Mode)
8. Measure Of Dispersion(Variance, Standard Deviation)
9. Population Mean And Sample Mean
10. What is a distribution and types of distributions?
11. Sampling Method And Its Types
12. What is a variable? and Random Variable?
13. Variable measurement scales
14. Frequency Distribution And Cumulative Frequency
15. What is a histogram?

1. Percentiles And Quantiles
2. IQR — InterQuantileRange
3. Box Plots
4. What is PDF ?
5. What is CDF?
6. What is a kernel?
7. What is kernel density estimation?
8. What is skewness?
9. Outliers and How to detect outliers
10. When/How to remove outliers?
11. Normal Distribution or Gaussian Distribution
12. What is Empirical Formula?
13. What is z-score?
14. How to calculate z-score? and z-score table
15. Standardization Vs Normalization
16. Standard Normal Distribution
17. Central Limit Theorem
18. Chebyshev’s Inequality
19. Covariance
20. Covariance Matrix
21. Pearson Correlation Coefficient
22. Spearman Correlation Coefficient

1. What are types of plots?
2. QQ-Plot
3. How to find if data is normally distributed?
4. Log normal distribution
5. Power law
6. Pareto distribution
7. What are transformations?
8. Box-Cox transform
9. Confidence Interval
10. Type-I and Type-II errors
11. One tailed and two tailed tests
12. What is Hypothesis testing?
13. What is p-value?
14. What is alpha?
15. What is critical value?
16. What is statistical significance?
17. What is a statistic?
18. What is a statistic test?
19. What is z-test and t-test?
20. Process of hypothesis test design
21. Analysis of variance (ANOVA)
22. Chi-squared test
23. What is causation?
24. Causation vs Correlation
25. What is conditional probability?
26. Bayes’ theorem
27. Binomial distribution and its applications
28. Various sampling methods
29. What is a statistic model?
30. What is statistical inference?