Course Description

A Calculus-based introduction to probability and the application of mathematical principles to the collection, analysis, and presentation of data. Modern probability concepts, discrete/ continuous models, and applications; estimation and statistical inference through modern parametric, nonparametric, and simulation/randomization methods; maximum likelihood; Bayesian methods. This course prepares students for the preliminary P/1 exam of the Society of Actuaries and Casualty Actuarial Society.

A Calculus-based introduction to probability and the application of mathematical principles to the collection, analys...

Course Outline

  1. 2015 Trial

    Description of this chapter

  2. 2

    Vectors and Data Frames

    In this lab, you'll learn how to create and access vectors and data frames in R.

  3. 4

    Probability & Counting

    After completing this chapter, you'll be able to simulate simple experiments to estimate probabilities.

  4. 6

    Binomial Distribution

    After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.

  5. 1

    Introduction to R

    In this lab, you'll learn the basics of R. You'll use R as a calculator and then assign some variables.

  6. 3

    Intro to Statistical Inference

    After completing this chapter, you'll be able to simulate simple experiments to estimate and interpret p-values.

  7. 5

    Counting & Permutation Tests

    After completing this chapter, you'll be able to apply counting rules to estimate likelihoods.

  8. 7

    Discrete Distributions

    After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.

  1. 2015 Trial

    Description of this chapter

  2. 1

    Introduction to R

    In this lab, you'll learn the basics of R. You'll use R as a calculator and then assign some variables.

  3. 2

    Vectors and Data Frames

    In this lab, you'll learn how to create and access vectors and data frames in R.

  4. 3

    Intro to Statistical Inference

    After completing this chapter, you'll be able to simulate simple experiments to estimate and interpret p-values.

  5. 4

    Probability & Counting

    After completing this chapter, you'll be able to simulate simple experiments to estimate probabilities.

  6. 5

    Counting & Permutation Tests

    After completing this chapter, you'll be able to apply counting rules to estimate likelihoods.

  7. 6

    Binomial Distribution

    After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.

  8. 7

    Discrete Distributions

    After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.

Course Instructor

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