Inferential statistics | Probability and Statistics | Khan Academy (English)

   Tuesday, September 13, 2022   

Starting a new Lecture Notes Series on Inferential statistics | Probability and Statistics | Khan Academy

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Inferential statistics | Probability and Statistics | Khan Academy
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Lecture Description of this above Topic:

Lecture 1: Hypothesis testing and p-values

Lecture 2: Sampling distribution example problem

Lecture 3: Large sample proportion hypothesis testing

Lecture 4: Pearson's chi square test (goodness of fit)

Lecture 5: k12.org exercise: Standard normal distribution and the empirical

Lecture 6: Z-statistics vs. T-statistics

Lecture 7: ck12.org normal distribution problems: Qualitative sense of normal distributions

Lecture 8: Small sample hypothesis testn

Lecture 9: ANOVA 1: Calculating SST (total sum of squares)

Lecture 10: Type 1 errors

Lecture 11: Sampling distribution of the sample mean

Lecture 12: Standard error of the mean

Lecture 13: Central limit theorem

Lecture 14: Small sample size confidence intervals

Lecture 15: Comparing population proportions 2

Lecture 16: Hypothesis test for difference of means

Lecture 17: Sampling distribution of the sample mean 2

Lecture 18: Mean and variance of Bernoulli distribution example

Lecture 19: ck12.org normal distribution problems: Empirical rule

Lecture 20: Margin of error 1

Lecture 21: Confidence interval example

Lecture 22: Difference of sample means distribution

Lecture 23: ck12.org normal distribution problems: z-score

Lecture 24: ANOVA 3: Hypothesis test with F-statistic

Lecture 25: Margin of error 2 | Inferential statistics

Lecture 26: Comparing population proportions 1

Lecture 27: Chi-square distribution introduction

Lecture 28: Hypothesis test comparing population proportions

Lecture 29: T-statistic confidence interval

Lecture 30: Introduction to the normal distribution

Lecture 31: Contingency table chi-square test

Lecture 32: Confidence interval of difference of means

Lecture 33: ck12.org: More empirical rule and z-score practice

Lecture 34: ANOVA 2: Calculating SSW and SSB (total sum of squares within and between)

Lecture 35: One-tailed and two-tailed tests

Lecture 36: Variance of differences of random variables

Lecture 37: Bernoulli distribution mean and variance formulas

Lecture 38: Clarification of confidence interval of difference of means

Lecture 39: Normal distribution excel exercise