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# STAT 300 - Modern Probability & Statistics

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## 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

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Description of this chapter

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2. 1

### Introduction to R

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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

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

4. 3

### Intro to Statistical Inference

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

5. 4

### Probability & Counting

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

6. 5

### Counting & Permutation Tests

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

7. 6

### Binomial Distribution

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

8. 7

### Discrete Distributions

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