Loved by learners at thousands of top companies:

whole-foods-grey.svg
airbnb-grey.svg
dell-grey.svg
mercedes-grey.svg
nielsen-grey.svg
siemens-grey.svg

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.

  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.

What do other learners have to say?

Devon

“I've used other sites, but DataCamp's been the one that I've stuck with.”

Devon Edwards Joseph

Lloyd's Banking Group

Louis

“DataCamp is the top resource I recommend for learning data science.”

Louis Maiden

Harvard Business School

Ronbowers

“DataCamp is by far my favorite website to learn from.”

Ronald Bowers

Decision Science Analytics @ USAA

Course Instructor

Icon Icon Icon professional info