• 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

Sample

By Jim Frost

A sample is a subset of the entire population. In inferential statistics, the goal is to use the sample to learn about the population. Consequently, the sample typically is selected in a manner that allows it to be an unbiased representation of the entire population. Drawing a random sample is a common method for achieving this unbiased representation. In a simple random sample, each member of the population has an equal probability of being included in the sample. However, different modifications of simple random samples can be used to meet specific research needs.

Related

Related Articles:
  • Simple Random Sampling
  • Systematic Sampling
  • Stratified Sampling
  • Cluster Sampling
  • How to Interpret P-values and Coefficients in Regression Analysis
  • How Hypothesis Tests Work: Significance Levels (Alpha) and P values
  • How To Interpret R-squared in Regression Analysis
  • Interpreting P values
  • How to Identify the Distribution of Your Data

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 eBook!

New! Buy My Hypothesis Testing eBook!

Buy My Regression eBook!

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
    • Popular
    • Latest
    Popular
    • How To Interpret R-squared in Regression Analysis
    • How to Interpret P-values and Coefficients in Regression Analysis
    • Measures of Central Tendency: Mean, Median, and Mode
    • Normal Distribution in Statistics
    • Multicollinearity in Regression Analysis: Problems, Detection, and Solutions
    • How to Interpret the F-test of Overall Significance in Regression Analysis
    • Understanding Interaction Effects in Statistics
    Latest
    • How to Find the P value: Process and Calculations
    • Sampling Methods: Different Types in Research
    • Beta Distribution: Uses, Parameters & Examples
    • Geometric Distribution: Uses, Calculator & Formula
    • What is Power in Statistics?
    • Conditional Distribution: Definition & Finding
    • Marginal Distribution: Definition & Finding

    Recent Comments

    • Hannah on How to Interpret Adjusted R-Squared and Predicted R-Squared in Regression Analysis
    • James on Introduction to Bootstrapping in Statistics with an Example
    • Jim Frost on Introduction to Bootstrapping in Statistics with an Example
    • Jim Frost on How To Interpret R-squared in Regression Analysis
    • Jim Frost on Comparing Regression Lines with Hypothesis Tests

    Copyright © 2022 · Jim Frost · Privacy Policy