• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
The Analysis Factor

The Analysis Factor

Statistical Consulting, Resources, and Statistics Workshops for Researchers

  • our programs
    • Membership
    • Online Workshops
    • Free Webinars
    • Consulting Services
  • statistical resources
  • blog
  • about
    • Our Team
    • Our Core Values
    • Our Privacy Policy
    • Employment
    • Collaborate with Us
  • contact
  • login

Power and Sample Size

How the Population Distribution Influences the Confidence Interval

by Jeff Meyer  Leave a Comment

Spoiler alert, real data are seldom normally distributed. How does the population distribution influence the estimate of the population mean and its confidence interval?

To figure this out, we randomly draw 100 observations 100 times from three distinct populations and plot the mean and corresponding 95% confidence interval of each sample.
[Read more…] about How the Population Distribution Influences the Confidence Interval

Tagged With: confidence interval, Estimated marginal Means, normal distribution, population, right skewed, sample, sample size, shape of distribution, standard deviation, Uniform distribution

Related Posts

  • How Confident Are You About Confidence Intervals?
  • How to Interpret the Width of a Confidence Interval
  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?
  • 5 Ways to Increase Power in a Study

Member Training: A Gentle Introduction to Bootstrapping

by TAF Support 

Bootstrapping is a methodology derived by Bradley Efron in the 1980s that provides a reasonable approximation to the sampling distribution of various “difficult” statistics. Difficult statistics are those where there is no mathematical theory to establish a distribution.

[Read more…] about Member Training: A Gentle Introduction to Bootstrapping

Tagged With: bootstrapping, distributions, sample size, sampling

Related Posts

  • Member Training: Power Analysis and Sample Size Determination Using Simulation
  • Member Training: Heterogeneity in Meta-analysis
  • How Big of a Sample Size do you need for Factor Analysis?
  • Member Training: The Fundamentals of Sample Size Calculations

How Big of a Sample Size do you need for Factor Analysis?

by Karen Grace-Martin  2 Comments

Most of the time when we plan a sample size for a data set, it’s based on obtaining reasonable statistical power for a key analysis of that data set. These power calculations figure out how big a sample you need so that a certain width of a confidence interval or p-value will coincide with a scientifically meaningful effect size.

But that’s not the only issue in sample size, and not every statistical analysis uses p-values.

[Read more…] about How Big of a Sample Size do you need for Factor Analysis?

Tagged With: Factor Analysis, p-value, rules of thumb, sample size

Related Posts

  • Member Training: A Gentle Introduction to Bootstrapping
  • Member Training: Matrix Algebra for Data Analysts: A Primer
  • Measurement Invariance and Multiple Group Analysis
  • Why Adding Values on a Scale Can Lead to Measurement Error

Member Training: Interpretation of Effect Size Statistics

by guest contributer 

Effect size statistics are required by most journals and committees these days ⁠— for good reason. 

They communicate just how big the effects are in your statistical results ⁠— something p-values can’t do.

But they’re only useful if you can choose the most appropriate one and if you can interpret it.

This can be hard in even simple statistical tests. But once you get into  complicated models, it’s a whole new story. [Read more…] about Member Training: Interpretation of Effect Size Statistics

Tagged With: Cohen's d, Correlation, correlation indexes, effect size, effect size statistics, empirically derived, Glass, Hedges, interpreting, null hypothesis, probability of superiority, Proportion, strength association, superiority, variance

Related Posts

  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?
  • Member Training: An Overview of Effect Size Statistics and Why They are So Important
  • Member Training: Inference and p-values and Statistical Significance, Oh My!
  • Member Training: Confusing Statistical Terms

How Confident Are You About Confidence Intervals?

by Jeff Meyer  6 Comments

Any time you report estimates of parameters in a statistical analysis, it’s important to include their confidence intervals.

How confident are you that you can explain what they mean? Even those of us who have a solid understand of confidence intervals get tripped up by the wording.

The Wording for Describing Confidence Intervals

Let’s look at an example. [Read more…] about How Confident Are You About Confidence Intervals?

Tagged With: confidence interval, estimate sample sizes, sample size

Related Posts

  • How the Population Distribution Influences the Confidence Interval
  • How to Interpret the Width of a Confidence Interval
  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?
  • The Effect Size: The Most Difficult Step in Calculating Sample Size Estimates

How to Interpret the Width of a Confidence Interval

by Christos Giannoulis  2 Comments

One issue with using tests of significance is that black and white cut-off points such as 5 percent or 1 percent may be difficult to justify.

Significance tests on their own do not provide much light about the nature or magnitude of any effect to which they apply.

One way of shedding more light on those issues is to use confidence intervals. Confidence intervals can be used in univariate, bivariate and multivariate analyses and meta-analytic studies.

[Read more…] about How to Interpret the Width of a Confidence Interval

Tagged With: Bivariate Statistics, confidence interval, multivariate analysis, sample size, standard error, Univariate statistics

Related Posts

  • How the Population Distribution Influences the Confidence Interval
  • How Confident Are You About Confidence Intervals?
  • The Difference Between Association and Correlation
  • Member Training: Statistical Rules of Thumb: Essential Practices or Urban Myths?

  • Go to page 1
  • Go to page 2
  • Go to page 3
  • Go to page 4
  • Go to Next Page »

Primary Sidebar

This Month’s Statistically Speaking Live Training

  • Member Training: The Link Between ANOVA and Regression

Upcoming Workshops

    No Events

Upcoming Free Webinars

TBA

Quick links

Our Programs Statistical Resources Blog/News About Contact Log in

Contact

Upcoming

Free Webinars Membership Trainings Workshops

Privacy Policy

Search

Copyright © 2008–2023 The Analysis Factor, LLC.
All rights reserved.

The Analysis Factor uses cookies to ensure that we give you the best experience of our website. If you continue we assume that you consent to receive cookies on all websites from The Analysis Factor.
Continue Privacy Policy
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Non-necessary
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.
SAVE & ACCEPT