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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.

  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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  2. 2

    Introduction to Inference

    In this chapter, you will learn about the central limit theorem in practice.
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  3. 3

    Confidence Intervals and p-Values

    In this chapter, you will learn about confidence intervals and p-values using actual polls from the 2016 US Presidential election.
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  4. 4

    Statistical Models

    In this chapter, you will learn about different types of probability models
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  5. 5

    Bayesian Statistics

    In this chapter, you will learn about Bayesian statistics.
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  6. 6

    Election Forecasting

    In this chapter, you will learn about election forecasting by exploring data from the 2016 US Presidential Election.
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  7. 7

    The t-distribution

    In this chapter, you will learn about the t-distribution.
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  8. 8

    Association and Chi-Squared Tests

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