• Skip to secondary menu
  • Skip to main content
  • Skip to primary sidebar
  • My Store
  • Glossary
  • Home
  • About Me
  • Contact Me

Statistics By Jim

Making statistics intuitive

  • Graphs
  • Basics
  • Hypothesis Testing
  • Regression
  • ANOVA
  • Probability
  • Time Series
  • Fun

Probability

Weibull Distribution: Uses, Parameters & Examples

By Jim Frost 6 Comments

What is a Weibull Distribution?

The Weibull distribution is a continuous probability distribution that can fit an extensive range of distribution shapes. Like the normal distribution, the Weibull distribution describes the probabilities associated with continuous data. However, unlike the normal distribution, it can also model skewed data. In fact, its extreme flexibility allows it to model both left- and right-skewed data. [Read more…] about Weibull Distribution: Uses, Parameters & Examples

Filed Under: Probability Tagged With: conceptual, distributions, graphs

Poisson Distribution: Definition & Uses

By Jim Frost 11 Comments

What is the Poisson Distribution?

The Poisson distribution is a discrete probability distribution that describes probabilities for counts of events that occur in a specified observation space. It is named after Siméon Denis Poisson.

In statistics, count data represent the number of events or characteristics over a given length of time, area, volume, etc. For example, you can count the number of cigarettes smoked per day, meteors seen per hour, the number of defects in a batch, and the occurrence of a particular crime by county. [Read more…] about Poisson Distribution: Definition & Uses

Filed Under: Probability Tagged With: conceptual, distributions, graphs

Using Combinations to Calculate Probabilities

By Jim Frost 6 Comments

Combinations in probability theory and other areas of mathematics refer to a sequence of outcomes where the order does not matter. For example, when you’re ordering a pizza, it doesn’t matter whether you order it with ham, mushrooms, and olives or olives, mushrooms, and ham. You’re getting the same pizza! [Read more…] about Using Combinations to Calculate Probabilities

Filed Under: Probability Tagged With: analysis example, choosing analysis, conceptual

Using Permutations to Calculate Probabilities

By Jim Frost 8 Comments

Permutations in probability theory and other branches of mathematics refer to sequences of outcomes where the order matters. For example, 9-6-8-4 is a permutation of a four-digit PIN because the order of numbers is crucial. When calculating probabilities, it’s frequently necessary to calculate the number of possible permutations to determine an event’s probability.

In this post, I explain permutations and show how to calculate the number of permutations both with repetition and without repetition. Finally, we’ll work through a step-by-step example problem that uses permutations to calculate a probability. [Read more…] about Using Permutations to Calculate Probabilities

Filed Under: Probability Tagged With: analysis example, choosing analysis, conceptual

Multiplication Rule for Calculating Probabilities

By Jim Frost 7 Comments

The multiplication rule in probability allows you to calculate the probability of multiple events occurring together using known probabilities of those events individually. There are two forms of this rule, the specific and general multiplication rules.

In this post, learn about when and how to use both the specific and general multiplication rules. Additionally, I’ll use and explain the standard notation for probabilities throughout, helping you learn how to interpret it. We’ll work through several example problems so you can see them in action. There’s even a bonus problem at the end! [Read more…] about Multiplication Rule for Calculating Probabilities

Filed Under: Probability Tagged With: analysis example, choosing analysis, conceptual

Using Contingency Tables to Calculate Probabilities

By Jim Frost 18 Comments

Contingency tables are a great way to classify outcomes and calculate different types of probabilities. These tables contain rows and columns that display bivariate frequencies of categorical data. Analysts also refer to contingency tables as crosstabulation (cross tabs), two-way tables, and frequency tables.

Statisticians use contingency tables for a variety of reasons. I love these tables because they both organize your data and allow you to answer a diverse set of questions. In this post, I focus on using them to calculate different types of probabilities. These probabilities include joint, marginal, and conditional probabilities. [Read more…] about Using Contingency Tables to Calculate Probabilities

Filed Under: Probability Tagged With: analysis example, conceptual

Probability Definition and Fundamentals

By Jim Frost 10 Comments

What is Probability?

The definition of probability is the likelihood of an event happening. Probability theory analyzes the chances of events occurring. You can think of probabilities as being the following:

  • The long-term proportion of times an event occurs during a random process.
  • The propensity for a particular outcome to occur.

Common terms for describing probabilities include likelihood, chances, and odds. [Read more…] about Probability Definition and Fundamentals

Filed Under: Probability Tagged With: conceptual

  • « Go to Previous Page
  • Go to page 1
  • Go to page 2

Primary Sidebar

Meet Jim

I’ll help you intuitively understand statistics by focusing on concepts and using plain English so you can concentrate on understanding your results.

Read More...

Buy My Introduction to Statistics Book!

Cover of my Introduction to Statistics: An Intuitive Guide ebook.

Buy My Hypothesis Testing Book!

Cover image of my Hypothesis Testing: An Intuitive Guide ebook.

Buy My Regression Book!

Cover for my ebook, Regression Analysis: An Intuitive Guide for Using and Interpreting Linear Models.

Subscribe by Email

Enter your email address to receive notifications of new posts by email.

    I won't send you spam. Unsubscribe at any time.

    Follow Me

    • FacebookFacebook
    • RSS FeedRSS Feed
    • TwitterTwitter

    Top Posts

    • How to Interpret P-values and Coefficients in Regression Analysis
    • How To Interpret R-squared in Regression Analysis
    • Mean, Median, and Mode: Measures of Central Tendency
    • Multicollinearity in Regression Analysis: Problems, Detection, and Solutions
    • How to do t-Tests in Excel
    • How to Find the P value: Process and Calculations
    • Interpreting Correlation Coefficients
    • Z-table
    • Choosing the Correct Type of Regression Analysis
    • Difference between Descriptive and Inferential Statistics

    Recent Posts

    • Monte Carlo Simulation: Make Better Decisions
    • Principal Component Analysis Guide & Example
    • Fishers Exact Test: Using & Interpreting
    • Percent Change: Formula and Calculation Steps
    • X and Y Axis in Graphs
    • Simpsons Paradox Explained

    Recent Comments

    • Jim Frost on Monte Carlo Simulation: Make Better Decisions
    • Gilberto on Monte Carlo Simulation: Make Better Decisions
    • Sultan Mahmood on Linear Regression Equation Explained
    • Sanjay Kumar P on What is the Mean and How to Find It: Definition & Formula
    • Dave on Control Variables: Definition, Uses & Examples

    Copyright © 2023 · Jim Frost · Privacy Policy