Introduction to Data Science Daily Overview: Unit 2
Unit 2
Daily Overview: Unit 2
Theme | Day | Lessons and Labs | Campaign | Topics | Page |
---|---|---|---|---|---|
What Is Your True Color? (10 days) |
1^+ | Lesson 1: What Is Your True Color? | Personality Color - data | Subsets, relative frequency | 119 |
2 | Lesson 2: What Does Mean Mean? | Personality Color | Measures of center – mean | 122 | |
3 | Lesson 3: Median In the Middle | Personality Color | Measures of center – median | 126 | |
4 | Lesson 4: How Far Is It from Typical? | Personality Color | Measures of spread – MAD | 129 | |
5 | Lab 2A: All About Distributions | Personality Color | Measures of center & spread – mean, median, MAD | 132 | |
6 | Lesson 5: Human Boxplots | Boxplots, IQR | 134 | ||
7 | Lesson 6: Face Off | Comparing distributions | 137 | ||
8 | Lesson 7: Plot Match | Comparing distributions | 140 | ||
9 | Lab 2B: Oh, the Summaries… | Personality Color | Boxplots, IQR, numerical summaries, custom functions | 143 | |
10 | Practicum: The Summaries | Food Habits or Time Use | Data cycle, comparing distributions | 146 | |
How Likely Is It? (7 days) |
11 | Lesson 8: How Likely is It? | Probability, simulations | 149 | |
12 | Lesson 9: Dice Detective | Simulations to detect unfairness | 152 | ||
13 | Lesson 10: Marbles, Marbles | Probability, with replacement | 156 | ||
14 | Lab 2C: Which Song Plays Next? | Probability of simple events, do loops, set.seed() | 158 | ||
15 | Lesson 11: This AND/OR That | Compound probabilities | 161 | ||
16 | Lab 2D: Queue It Up! | Probability with & without replacement, sample() | 165 | ||
17 | Practicum: Win, Win, Win | Probability estimation through repeated simulations | 168 | ||
Are You Stressing or Chilling? (8 Days) |
18^ | Lesson 12: Don’t Take My Stress Away | Stress/Chill – data | Introduction to campaign | 171 |
19 | Lesson 13: The Horror Movie Shuffle | Stress/Chill – data | Chance differences – categorical variables | 175 | |
20 | Lab 2E: The Horror Movie Shuffle | Stress/Chill – data | Inference for categorical variable, do loops, shuffle() | 179 | |
21 | Lesson 14: The Titanic Shuffle | Stress/Chill – data | Chance differences – numerical variables | 182 | |
22 | Lab 2F: The Titanic Shuffle | Stress/Chill – data | Inference for numerical variable, do loops, shuffle() | 186 | |
23+ | Lesson 15: Tangible Data Merging | Stress/Chill – data | Merging datasets | 188 | |
24 | Lab 2G: Getting It Together | Stress/Chill & Personality Color | Merging datasets, stacking vs. joining | 192 | |
25 | Practicum: What Stresses Us? | Stress/Chill & Personality Color | Analyzing merged data | 192 | |
What’s Normal? (5 Days) |
26 | Lesson 16: What Is Normal? | Introduction to normal curve | 194 | |
27 | Lesson 17: Normal Measure of Spread | Measures of spread - SD | 197 | ||
28 | Lesson 18: What’s Your Z-Score? | z-scores, shuffling | 200 | ||
29 | Lab 2H: Eyeballing Normal | Normal curves overlaid on distributions & simulated data | 204 | ||
30 | Lab 2I: R’s Normal Distribution Alphabet | Normal probability, rnorm(), pnorm(), quantiles, qnorm() | 206 | ||
Unit 2 Project (5 Days) |
31-35 | End of Unit Project and Presentations: Asking and Answering Statistical Investigative Questions of Our Data | Stress/Chill, Personality Color, Food Habits, or Time Use | Synthesis of above | 208 |
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