Introduction to Inferential Statistics

1 Introduction
2 Game Plan for Descriptive Statistics
3 Variable Types in Statistics
4 Population vs. Sample
5 CASE STUDY Briefing – Moneyball
6 Python – Setting Up
7 Measures of Central Tendency
8 (Arithmetic) Mean
9 Python – Mean
10 EXERCISE – Mean
11 Median
12 Python – Median
13 EXERCISE – Median
14 Mode
15 Python – Mode
16 EXERCISE – Mode
17 Standard Deviation and Variance
18 Python – Standard Deviation and Variance
19 EXERCISE – Standard Deviation and Variance
20 Coefficient of Variation
21 EXERCISE – Coefficient of Variation
22 Python – Coefficient of Variation
23 Covariance
24 Python – Covariance
25 EXERCISE – Covariance
26 Correlation
27 Python – Correlation
28 EXERCISE – Correlation
29 Normal Distribution
30 Python – Normal Distribution
31 EXERCISE – Normal Distribution
32 CASE STUDY – Moneyball
33 Wrap Up – Descriptive Statistics
34 Game Plan for Confidence Intervals
35 CASE STUDY Briefing – Dioguinis Pizza
36 Standard Error of the Sample Mean
37 Python – Libraries and Data
38 Python – Standard Error of the Sample Mean
39 Z-Score and Standardization
40 Python – Z-Score and Standardization
41 Confidence Level
42 Python – Confidence Level
43 Confidence Intervals for Large Samples
44 Python – Confidence Interval for Large Samples
45 EXERCISE – Confidence Interval Function with ChatGPT
46 CASE STUDY – Guinness Beer and t-distribution
47 Degrees of Freedom
48 Confidence Interval with Small Samples
49 Python – Confidence Interval with Small Samples
50 EXERCISE – Confidence Interval Function with ChatGPT
51 Confidence Intervals Wrap Up
52 Project Presentation – Lights, Camera, Statistics
53 Python – Data Preparation and Cleaning
54 Python – Exploratory Data Analysis
55 Python – Estimating Average Ratings
56 Python – Conclusions
57 Game Plan for Hypothesis Testing
58 What is Hypothesis Testing?
59 P-Value
60 Type I and Type II Errors
61 CASE STUDY – Publication Bias in Statistics
62 How to Test Your Hypothesis (Known Population Variance).
63 CASE STUDY Briefing – Tesla Production
64 Python – Setting Up and Libraries
65 Python – How to Test Your Hypothesis (Known Population Variance)
66 Python – Build a Function to Test Your Known Variance Hypothesis
67 Hypothesis Testing with Unknown Population Variance
68 Python – How to Test Your Hypothesis (Unknown Population Variance) – Part 1
69 Python – How to Test Your Hypothesis (Unknown Population Variance) – Part 2
70 Paired T-Test
71 Python – Paired T-Test – Part 1
72 Python – Paired T-Test – Part 2
73 Two Sample T-Test
74 Python – Levene’s Test
75 Python – Welch’s T-Test
76 Python – Two-Sample T-Test
77 Exercise – Two-Sample Test Function
78 One-Tailed Test vs. Two-Tailed Test
79 Python – One-Tailed Test with Known Variance
80 Python – One-Tailed Test with Unknown Variance
81 Python – One-Tailed Paired T-Test
82 Python – One-Tailed Two-Sample T-Test
83 Chi-Square Test
84 Python – Chi-Square Test
85 Is Your Distribution Normal? – The Shapiro-Wilks Test
86 Python – Shapiro-Wilks Test
87 Powerposing and P-Hacking
88 Hypothesis Testing Wrap Up
89 Capstone Project with ChatGPT – Yelp me!
90 Python Solutions – Data
91 Python Solutions – Hypothesis 1
92 Python Solutions – Hypothesis 2
93 Python Solutions – Hypothesis 3
94 Game Plan for Advanced Hypothesis Testing
95 Python – Setup
96 Mann-Whitney U Test
97 Python – Box plot for Normality
98 Python – Shapiro Wilks Test
99 D’Agostino and Pearson Test
100 Python – D’Agostino and Pearson Test
101 Python – Mann-Whitney U Test
102 ANOVA
103 Python – ANOVA
104 Python – D’Agostino and Pearson Test
105 Kruskal-Wallis Test
106 Python – Kruskal-Wallis Test
107 Spearman Correlation
108 Python – Spearman Correlation
109 Wilcoxon Signed-Rank Test
110 Python – Wilcoxon Signed-Rank Test
111 Key Learnings and Outcomes – Advanced Hypothesis Testing
112 Let’s Keep Learning Together!