Statistics Lectures - 9: Permutations & Combinations

A series of free Statistics Lectures with lessons, examples & solutions in videos.

This is the ninth page of the series of free video lessons, “Statistics Lectures”. These lectures discuss permutations and combinations.

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Statistics - Lecture 24: Permutations

Statistics - Lecture 25: Combinations

Statistics Lecture Series - Table Of Contents

Descriptive Statistics
1: The Basics: Descriptive And Inferential Statistics
2: Sampling Methods

3: Types Of Variables
4: Independent And Dependent Variables
5: Variable Measurement Scales

6: Frequency Distributions And Cumulative Frequency Distributions
7: Bar Graphs And Pie Charts
8: Histograms And Stem & Leaf Plots

9: Arithmetic Mean For Samples And Populations
10: Central Tendency: Mean, Median And Mode

11: Measures Of Dispersion: Variance And Standard Deviation Of A Population
12: Variance And Standard Deviation Of A Sample
13: Percentiles And Quartiles
14: The Five Number Summary, Interquartile Range (IQR), And Boxplots
15: The Effects Of Outliers

16: Skewness
17: The Normal Curve And Empirical Rule

18: Z-Scores (Part 1)
19: Z-Scores (Part 2)
20: Extra Z-Score Problems
Probability
21: The Basics Of Probability
22: Addition Rule
23: Multiplication Rule

24: Permutations
25: Combinations

26: Discrete And Continuous Random Variables
27: Discrete Probability Distributions
28: Probability Histograms
29: Mean and Expected Value of Discrete Random Variables
30: Variance and Standard Deviation of Discrete Random Variables

31: The Law Of Large Numbers
32: Binomial Distribution
33: Mean And Standard Deviation Of Binomial Random Variables

34: Poisson Distribution/Process
35: Mean And Standard Deviation of Poisson Random Variables
Correlation
36: Scatter Plots
37: Pearson's r Correlation
38: Hypothesis Testing With Pearson's r

39: Linear Regression
40: Spearman Correlation
41: Correlation vs. Causation
Inferential Statistics
42: Parameters, Statistics And Sampling Error
43: Distribution Of The Sample Mean
44: The Central Limit Theorem

45: Sample Proportions
46: Confidence Intervals About The Mean With Population Standard Deviation Known
47: Calculating Required Sample Size To Estimate Population Mean

48: Student's t-Distribution
49: Confidence Intervals About The Mean, Population Standard Deviation Unknown
50: Confidence Intervals For Population Proportions
51: Calculating Required Sample Size To Estimate Population Proportions

52: Null And Alternative Hypotheses
53: Type I and Type II Errors
54: One-Tailed And Two-Tailed Tests

55: Effect Size
56: Power
57: Statistical Vs. Practical Significance
58: Independent And Dependent Samples

59: One Sample z-Test
60: One Sample z-Test for Proportions
61: One Sample t-Test

62: Independent Samples t-Test
63: Confidence Intervals For Independent Samples t-Test
64: Effect Size For Independent Samples t-Test
65: Dependent Samples t-Test

66: Confidence Intervals For Dependent Samples t-Test
67: Effect Size For Dependent Samples t-Test
68: z-Test for Proportions, Two Samples
69: Confidence Intervals For The Difference Of Two Proportions

70: Introduction To Analysis Of Variance (ANOVA)
71: One-Way ANOVA
72: Effect Size For One-Way ANOVA
73: Post-Hoc Tests For One-Way ANOVA
74: Repeated-Measures ANOVA
75: Factorial ANOVA, Two Independent Factors
76: Factorial ANOVA, Two Dependent Factors
77: Factorial ANOVA, Two Mixed Factors

78: Chi-Square Test for Goodness of Fit
79: Chi-Square Test for Independence
80: Mann-Whitney U-Test
81: Wilcoxon Signed-Ranks Test
82: The Kruskal-Wallis Test
83: The Friedman Test

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