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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.
Description of this chapter
In this lab, you'll learn how to create and access vectors and data frames in R.
After completing this chapter, you'll be able to simulate simple experiments to estimate probabilities.
After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.
In this lab, you'll learn the basics of R. You'll use R as a calculator and then assign some variables.
After completing this chapter, you'll be able to simulate simple experiments to estimate and interpret p-values.
After completing this chapter, you'll be able to apply counting rules to estimate likelihoods.
After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.
Description of this chapter
In this lab, you'll learn the basics of R. You'll use R as a calculator and then assign some variables.
In this lab, you'll learn how to create and access vectors and data frames in R.
After completing this chapter, you'll be able to simulate simple experiments to estimate and interpret p-values.
After completing this chapter, you'll be able to simulate simple experiments to estimate probabilities.
After completing this chapter, you'll be able to apply counting rules to estimate likelihoods.
After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.
After completing this chapter, you'll be able to calculate probabilities under the Binomial Distribution.
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