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# HarvardX Data Science Module 4 - Inference and Modeling

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## Course Description

Learn inference and modeling - two of the most widely used statistical tools in data analysis.

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1. 1

### Parameters and Estimates

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In this chapter, you will learn about parameters and estimates using the example of election polling.

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Exercise 1. Polling - expected value of S
50 xp
Exercise 2. Polling - standard error of S
50 xp
Exercise 3. Polling - expected value of X-bar
50 xp
Exercise 4. Polling - standard error of X-bar
50 xp
Exercise 5. se versus p
100 xp
Exercise 6. Multiple plots of se versus p
100 xp
Exercise 7. Expected value of d
50 xp
Exercise 8. Standard error of d
50 xp
Exercise 9. Standard error of the spread
100 xp
Exercise 10. Sample size
50 xp
End of Assessment
50 xp
2. 3

### Confidence Intervals and p-Values

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In this chapter, you will learn about confidence intervals and p-values using actual polls from the 2016 US Presidential election.

3. 6

### Election Forecasting

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In this chapter, you will learn about election forecasting by exploring data from the 2016 US Presidential Election.

4. 7

### The t-distribution

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In this chapter, you will learn about the t-distribution.

5. 8

### Association and Chi-Squared Tests

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In this chapter, you will learn about the association tests and the chi-square test.

datasets

Weston Stearns

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