Introduction to Data Science Daily Overview: Unit 4

Unit 4

Daily Overview: Unit 4

Theme	Day	Lessons and Labs	Campaign	Topics	Page
Predictions and Models (15 days)	1	Lesson 1: Water Usage		Data cycle, official data sets	315
	2	Lesson 2: Exploring Water Usage		Exploratory data analysis, campaign creation	319
	3	Lesson 3: Evaluating and Implementinga Water Campaign	Water Campaign—data	Statistical questions, evaluate & mock implement campaign	321
	4	Lesson 4: Refining the Water Campaign	Water Campaign—data	Revise and edit campaign, data collection	323
	5	Lesson 5: Statistical Predictions Using One Variable	Water Campaign—data	One-variable predictions using a rule	325
	6	Lesson 6: Statistical Predictions by Applying the Rule	Water Campaign—data	Predictions applying mean square deviation, mean absolute error	328
	7	Lesson 7: Statistical Predictions Using Two Variables	Water Campaign—data	Two-variable statistical predictions, scatterplots	333
	8	LAB 4A: If the Line Fits…	Water Campaign—data	Estimate line of best fit	335
	9	LAB 4B: What’s the Score?	Water Campaign—data	Comparing predictions to real data	337
	10	Lesson 8: What’s the Trend?	Water Campaign—data	Trend, associations, linear model	339
	11	Lesson 9: Spaghetti Line	Water Campaign—data	Estimate line of best fit, single linear regression	343
	12	LAB 4C: Cross-Validation	Water Campaign—data	Use training and testing data for predictions	346
	13	Lesson 10: Predicting Values	Water Campaign—data	Predictions based on linear models	348
	14	Lesson 11: How Strong Is It?	Water Campaign—data	Correlation coefficient, strength of trend	351
	15	LAB 4D: Interpreting Correlations	Water Campaign—data	Use correlation coefficient to determine best model	353
Piecing it Together (6 days)	16	Lesson 12: More Variables to Make Better Predictions	Water Campaign—data	Multiple linear regression	358
	17	Lesson 13: Combination of Variables	Water Campaign—data	Multiple linear regression	361
	18	LAB 4E: This Model Is Big Enough for All of Us	Water Campaign—data	Multiple linear regression	364
	19	Practicum: Predictions	Water Campaign—data	Linear regression	365
	20	Lesson 14: Improving Your Model	Water Campaign—data	Non-linear regression	366
	21	LAB 4F: Some Models Have Curves	Water Campaign—data	Non-linear regression	368
The Growth of Landfills (5 days)	22	Lesson 15: The Growth of Landfills	Water Campaign—data	Modeling to answer realworld problems	372
	23	Lesson 16: Exploring Trash via the Dashboard	Water Campaign—data	Analyze data to improve models	376
	24	Lesson 17: Exploring Trash via RStudio	Water Campaign—data	Analyze data to improve models	377
	25	Prepare Team Presentations	Water Campaign—data	Modeling with statistics	-
	26	Present Team Recommendations	Water Campaign—data	Modeling with statistics	-
Decisions, Decisions! (3 days)	27	Lesson 18: Grow Your Own Decision Tree	Water Campaign—data	Multiple predictors, classifying into groups, decision trees	380
	28	Lesson 19: Data Scientists or Doctors?	Water Campaign—data	Decision trees based on training and testing data	385
	29	LAB 4G: Growing Trees	Water Campaign—data	Decision trees to classify observations	388
Ties that Bind (3 days)	30	Lesson 20: Where Do I Belong?	Water Campaign—data	Clustering, k-means	392
	31	LAB 4H: Finding Clusters	Water Campaign—data	Clustering, k-means	397
	32+	Lesson 21: Our Class Network	Water Campaign—data	Clustering, networks	399
End of Unit Project (7 days)	33- 40	End of Unit 3 and 4 Design Project andOral Presentations: Water Usage	Water Campaign	Synthesis of above	403

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