Skip to main content
Ctrl+K
Probability and Statistics - Home
  • Course Notes: Probability and Statistics

Probability

  • Basic Probability
    • Probability Playground
    • Exercises
    • Solutions to Exercises
  • Counting Patterns
  • Compound Events
  • Partitions
  • Conditional Probability
    • Excercises
    • Solutions to Exercises
  • Discrete Probability Functions
    • Exercises
    • Solutions to Selected Exercises
  • Expected Value
  • Excercises
    • 50 Counting Questions
    • 50 Probability Questions
    • 85 More Probability Questions

Statistics

  • Basics of Statistics and R
    • Exploratory Data Analysis
    • Statistics Formula Sheet
    • Sampling Functions
  • Sampling Distributions, the Central Limit Theorem and the Law of Large Numbers
    • The Central Limit Theorem and Estimation of the Mean
    • Sampling Distributions Examples
  • Normal Curve
    • Calculations with the Normal Curve
    • The \(z\)-Proportion Test
  • \(t\)-Tests
    • The \(t\)-Test
    • Independent Samples \(t\)-Test
    • Matched Pairs \(t\)-Test
    • Small Samples and \(t\)-Tests
  • Proportion Testing
    • The \(\chi^2\) Test of Independence
    • Goodness of Fit (GOF)
  • ANOVA
  • Correlation and Regression
  • Statistical Estimation

Appendix

  • Overview, Index, Links
  • Statistical Formulas
  • Helpful Code
    • Extracting Columns from Data Frames as Vectors
    • Subsetting a Data Frame
    • Creating a Data Frame
    • Grid of Graphics
  • Poker Primer
  • Binder
  • .ipynb

Overview, Index, Links

Contents

  • Index of Appendix Pages

Overview, Index, Links#

We utilize the open source freeware R in this course.

When using R, several tasks are used quite often without a detailed explanation given for each use. We therefore have created a reference page for the most common uses. We have several pages in this section that deal with typical issues and the code in R that gets around them.

Index of Appendix Pages#

The following list describes the contents of each page:

  1. Statistical Formulas: Key notation for understanding R commands and statistical models.

  2. Helpful Code: Basic tasks in R like calculating standard descriptives and the 5-Number Summary along with using the cat() function to display text and code output together.

  3. Extracting Columns from Data Frames as Vectors: In a large data set, this single operation is used quite often to grab vectors of data we wish to analyze.

  4. Subsetting a Data Frame: Using the subset() function to extract specific types of data points from a data frame.

  5. Creating a Data Frame: Entering data into R by creatinng vectors using the concatenate function c() and then joining them into a dataframe.

  6. Creating a Grid of Graphics: When displaying multiple graphical objects at once, we can use the layout() and matrix() functions to create a grid. The graphical objects will be reduced in size and laid out as we specify. The result saves space and helps to organize content in a more meaningful way.

previous

Statistical Estimation

next

Statistical Formulas

Contents
  • Index of Appendix Pages

By Robb Sinn

© Copyright 2024.