Statistics Bootcamp (with Python): Zero to Mastery

20h 50m 51s
English
Paid
May 20, 2024

Learn Statistics from an industry expert (and even have fun). You'll learn by building 6 statistics-based projects and solidify your skills with 18 quizzes, practice tests, and challenges. Plus you'll learn to utilize ChatGPT to work with statistics and conduct data analysis efficiently.

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We guarantee you this is the most up-to-date, comprehensive, and FUN way to learn Statistics with Python. This Statistics course is the key building block to launch your career in statistics-heavy fields like Data Analytics, Data Science, and A.I. Machine Learning.

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# Title Duration
1 Learn Statistics with Diogo Resende 01:14
2 Course Outline 02:50
3 Why Statistics Matter - The Challenger Space Shuttle Disaster 03:31
4 Creating a Google Account 05:24
5 Setting Up the Course Materials 03:24
6 Game Plan for Python Essentials 01:54
7 Print Function 05:48
8 Python - Print Function 10:28
9 Input Function 04:20
10 Python - Input Function 08:09
11 CHALLENGE - Your Superhero Name 06:51
12 Variable Types 03:02
13 Python - Variable Types 06:27
14 Arithmetic Operators 06:04
15 Python - Arithmetic Operators 06:48
16 Comparison Operators 03:41
17 Python - Comparison Operators 04:57
18 CHALLENGE - Split Bill Calculator 11:29
19 The if-else Condition 06:22
20 Python - if-else Conditions 06:02
21 EXERCISE - Can You Vote? 02:29
22 EXERCISE - Grading Papers 05:22
23 CHALLENGE - Berghain Club Bouncer 11:55
24 CHALLENGE - Your Monthly Savings Plan 19:44
25 Wrap Up - Python Essentials 02:22
26 Game Plan for Intermediate Python for Statistics 03:08
27 While Loop 02:27
28 Python - While Loops 06:45
29 EXERCISE - Countdown Times 05:03
30 Python Lists 07:01
31 Python - Lists 10:31
32 EXERCISE - Monthly Expense Report 06:43
33 EXERCISE - Fibonacci Sequence 06:07
34 Randomization 04:36
35 Python - Randomization 05:25
36 EXERCISE - Movie Picker 06:22
37 CHALLENGE - Read my Mind 09:01
38 Dictionaries 04:03
39 Python - Dictionaries 06:31
40 EXERCISE - Magical Pet Sounds 07:36
41 CHALLENGE - Budget Mastermind 16:20
42 For Loops 04:42
43 Python - For Loops 04:19
44 EXERCISE - Sum of Numbers 04:27
45 EXERCISE - Counting the Number of Characters 07:59
46 CHALLENGE - Treasure Hunter 14:09
47 Functions 06:49
48 Python - Functions 06:19
49 EXERCISE - Function That Adds Numbers 02:21
50 EXERCISE - Function That Counts Vowels 04:36
51 EXERCISE - Function That Transforms Fahrenheit to Celsius 06:35
52 CHALLENGE - Recipe Converter 24:41
53 Wrap Up - Python Intermediate Skills 03:24
54 Project Presentation - Virtual Escape Game 05:52
55 Python - Plan the Solution 08:16
56 Python - Check User's Answer Function 08:48
57 Python - Prepare Game 18:12
58 Python - Solving with ChatGPT 06:55
59 Game Plan for Descriptive Statistics 01:51
60 Variable Types in Statistics 02:56
61 Population vs. Sample 03:29
62 CASE STUDY Briefing - Moneyball 02:17
63 Python - Setting Up 05:52
64 Measures of Central Tendency 03:14
65 (Arithmetic) Mean 03:39
66 Python - Mean 04:45
67 EXERCISE - Python 02:36
68 Median 02:17
69 Python - Median 01:52
70 EXERCISE - Median 01:09
71 Mode 01:28
72 Python - Mode 02:35
73 EXERCISE - Mode 02:37
74 Standard Deviation and Variance 04:57
75 Python - Standard Deviation and Variance 05:27
76 EXERCISE - Standard Deviation and Variance 02:38
77 Coefficient of Variation 04:32
78 Python - Coefficient of Variation 03:26
79 EXERCISE - Coefficient of Variation 01:04
80 Covariance 04:15
81 Python - Covariance 03:48
82 EXERCISE - Covariance 01:52
83 Correlation 06:55
84 Python - Correlation 05:37
85 EXERCISE - Correlation 02:01
86 Normal Distribution 04:09
87 Python - Normal Distribution 06:48
88 EXERCISE - Normal Distribution 03:12
89 CASE STUDY - Moneyball 04:15
90 Wrap Up - Descriptive Statistics 01:56
91 Game Plan for Confidence Intervals 01:05
92 CASE STUDY Briefing - Dioguinis Pizza 01:30
93 Standard Error of the Sample Mean 02:18
94 Python - Libraries and Data 04:40
95 Python - Standard Error of the Sample Mean 02:48
96 Z-Score and Standardization 03:13
97 Python - Z-Score and Standardization 09:58
98 Confidence Level 04:50
99 Python - Confidence Level 10:31
100 Confidence Intervals for Large Samples 06:18
101 Python - Confidence Interval for Large Samples 06:13
102 EXERCISE - Confidence Interval Function with ChatGPT 06:56
103 CASE STUDY - Guinness Beer and t-distribution 02:36
104 Confidence Interval with Small Samples 03:27
105 Degrees of Freedom 07:14
106 Python - Confidence Interval with Small Samples 08:15
107 EXERCISE - Confidence Interval Function with ChatGPT 05:12
108 Confidence Intervals Wrap Up 04:28
109 Project Presentation - Lights, Camera, Statistics 02:41
110 Python - Data Preparation and Cleaning 20:53
111 Python - Exploratory Data Analysis 16:56
112 Python - Estimating Average Ratings 11:58
113 Python - Conclusions 05:44
114 Exercise: Imposter Syndrome 02:57
115 Game Plan for Hypothesis Testing 03:08
116 What is Hypothesis Testing? 04:55
117 P-Value 04:37
118 Type I and Type II Errors 04:06
119 CASE STUDY - Publication Bias in Statistics 02:59
120 How to Test Your Hypothesis (Known Population Variance). 06:51
121 CASE STUDY Briefing - Tesla Production 01:49
122 Python - Setting Up and Libraries 02:53
123 Python - How to Test Your Hypothesis (Known Population Variance) 12:01
124 Python - Build a Function to Test Your Known Variance Hypothesis 05:23
125 Hypothesis Testing with Unknown Population Variance 02:55
126 Python - How to Test Your Hypothesis (Unknown Population Variance) - Part 1 11:03
127 Python - How to Test Your Hypothesis (Unknown Population Variance) - Part 2 06:39
128 Paired T-Test 03:55
129 Python - Paired T-Test - Part 1 10:40
130 Python - Paired T-Test - Part 2 03:30
131 Two Sample T-Test 05:31
132 Python - Levene's Test 08:05
133 Python - Welch's T-Test 03:45
134 Python - Two-Sample T-Test 02:13
135 Exercise - Two-Sample Test Function 04:42
136 One-Tailed Test vs. Two-Tailed Test 05:51
137 Python - One-Tailed Test with Known Variance 07:28
138 Python - One-Tailed Test with Unknown Variance 05:40
139 Python - One-Tailed Paired T-Test 05:55
140 Python - One-Tailed Two-Sample T-Test 05:30
141 Chi-Square Test 03:09
142 Python - Chi-Square Test 11:00
143 Is Your Distribution Normal? - The Shapiro-Wilks Test 02:44
144 Python - Shapiro-Wilks Test 05:35
145 Hypothesis Testing Wrap Up 02:44
146 Powerposing and P-Hacking 03:40
147 Python Solutions - Data 14:42
148 Capstone Project with ChatGPT - Yelp me! 02:44
149 Python Solutions - Hypothesis 1 11:20
150 Python Solutions - Hypothesis 2 09:08
151 Python Solutions - Hypothesis 3 08:42
152 Game Plan for Multilinear Regression 01:23
153 CASE STUDY Briefing - Pricing Diamonds 01:54
154 Linear Regression 05:13
155 Python - Libraries and Data 04:21
156 Python - Exploratory Data Analysis 04:58
157 Python - Linear Regression 03:10
158 Regression Statistics 04:24
159 Python - Linear Regression Output 02:30
160 Python - Plotting Regression Curve 02:57
161 Dummy Variable (Trap) 04:01
162 Python - Linear Regression with Dummy Variables 06:53
163 EXERCISE - Create Function that Reads the Regression Coefficients with ChatGPT 07:11
164 CASE STUDY - Linearity Bias - We Will All Be Obese! Wait What? 04:02
165 Multilinear Regression 01:48
166 Python - Categorical Variables 05:48
167 Python - Multilinear Regression Preparation 02:11
168 Under and Overfitting 03:28
169 Training and Test Set 02:35
170 Python - Training and Test Split 03:15
171 Python - Multilinear Regression 08:43
172 Assessing Regression Models 06:08
173 Python - Assessing Regression Model 06:20
174 CASE STUDY - Dangers of Regression Analysis 02:52
175 Multilinear Regression Wrap Up 02:03
176 Capstone Project - Understanding Sales Drivers 01:08
177 Python - Solutions - Step 1 07:14
178 Python - Solutions - Steps 2-4 05:38
179 Python - Solutions - Steps 5-6 07:16
180 Game Plan for Logistic Regression 01:40
181 CASE STUDY Briefing - Spam Emails 01:26
182 Logistic Regression 03:29
183 Python - Preparing Script and Loading Data 03:32
184 Python - Summary Statistics 03:45
185 Python - Histograms and Outlier Detection 05:37
186 Python - Correlation Matrix 03:27
187 Python - Logistic Regression Preparation 04:00
188 How to Read Logistic Regression Coefficients 02:12
189 Python - Logistic Regression 02:18
190 Python - Build a Coefficient Function with ChatGPT 09:07
191 Python - Predictions 03:20
192 Confusion Matrix and Model Assessment 06:25
193 Python - Confusion Matrix and Classification Report 05:35
194 Python - Assessing Classification Models with ChatGPT 05:31
195 Section Wrap Up - Logistic Regression 03:16
196 Capstone Project - Surviving Titanic 01:34
197 Python - Libraries and Data with ChatGPT 08:13
198 Python - Removing Outliers and EDA with ChatGPT 12:35
199 Python - Logistic Regression Model and Assessment with ChatGPT 23:29
200 Game Plan for Cox Proportional Hazard Regression 02:15
201 Introduction to Survival Analysis 07:48
202 CASE STUDY - Briefing 01:48
203 Python - Libraries and Data 05:10
204 Kaplan-Meier Estimator 04:36
205 Python - Kaplan Meier Estimator 04:23
206 Python - Calculating for a Specific Event 02:47
207 Python - Plotting Kaplan-Meier and Cumulated Curves 03:52
208 Censoring 03:46
209 Log Rank Test 02:56
210 Python - Kaplan-Meier Estimator per Gender and Visualization 05:51
211 Python - Log Rank Test 06:34
212 Cox Proportional Hazard Regression 04:52
213 Python - Prepare Data for CPH Model 03:12
214 Python - Cox Proportional Hazard Regression 09:37
215 Python - Visualize Results 02:13
216 Assessing Cox Proportional Hazard Models 05:19
217 Python - Assessing the CPH Model 08:38
218 Python - Predicting Specific Instances 03:39
219 Cox Proportional Hazard Regression Wrap Up 03:15
220 Capstone Project - Will Your App Make it? 01:24
221 Python - Libraries and Data 07:11
222 Python - Data Cleaning 19:11
223 Python - Dependent Variable 08:27
224 Python - Kaplan-Meier Estimator 04:31
225 Python - Cox Model 10:01
226 Thank You! 01:18

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