# STAT 300 - Modern Probability & Statistics

72 Exercises

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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

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?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

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

Louis Maiden