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Search results “What is a statistical power analysis”

08:22
This video is the first in a series of videos related to the basics of power analyses. All materials shown in the video, as well as content from the other videos in the power analysis series can be found here: https://osf.io/a4xhr/

09:45

09:42
Views: 95627 NurseKillam

04:54
Learn the basic concepts of power and sample size calculations. With definitions for alpha levels and statistical power and effect size, a brief look at Stata's interface, and strategies for increasing statistical power, this video is a useful introduction for all subsequent power and sample size videos on the Stata Youtube Channel. Created using Stata 13; new features available in Stata 14. Copyright 2011-2017 StataCorp LLC. All rights reserved.
Views: 62123 StataCorp LLC

03:19
Definition of power, Type II errors, and sample size issues
Views: 55460 Keith Bower

08:40
This video present an example problem for finding the power of an experimental design.
Views: 7710 Matthew Novak

07:16
This video covers the types of errors you can commit when making conclusions about populations based on sample data (Type I and Type II errors), p-values, statistical power, and power analysis. To see an example of a power analysis for a study for which the data are analyzed using a two-sample t-test, check out my blog: https://www.biostatisticsbydesign.com/blog/2019/1/11/power-analysis-an-underutilized-tool If you'd like to contact me for a statistics consultation, fill out a request form here: https://www.biostatisticsbydesign.com/request-a-consultation/ Visit my website https://www.biostatisticsbydesign.com

29:19
If you are at a university other than UCSD and have found this or any of my other videos to be useful, please do me a favor and send me a note at [email protected] indicating your university affiliation and which videos you've found useful. Thank you! - Dr. Julian Parris ---- Tutorial on Visualizing and Calculating Statistical Power for simple hypothesis testing using z-tests.
Views: 38944 ProfessorParris

03:04
This video explains what statistical power is. Power = the probability of rejecting the null hypothesis when it is false. Click here for free access to all of our videos: https://www.youtube.com/user/statisticsinstructor (Remember to click on "Subscribe") Power Type I error Type II error Hypothesis testing in statistics

03:15
Illustration of how statistical power works, and how it can increase or decrease. Related blog post: http://www.andysbrainblog.blogspot.com/2013/02/the-will-to-fmri-power.html
Views: 16354 Andrew Jahn

17:28
http://thedoctoraljourney.com/ This tutorial focuses on the power of a statistical procedure and how power is maximized. For more statistics, research and SPSS tools, visit http://thedoctoraljourney.com/.
Views: 9502 The Doctoral Journey

21:29
Power and Sample Size Calculation Motivation and Concepts of Power/Sample Calculation, Calculating Power and Sample Size Using Formula, Software, and Power Chart
Views: 14660 Kunchok Dorjee

09:29
This video describes how you can use an online calculator to figure out how big your cell sizes should be for an experiment. The video uses SPSS to help determine the mean & standard deviation for your dependent variables. The online calculator completes the power analysis to show required cell size. The calculator used in this video is: https://www.statisticalsolutions.net/pssZtest_calc.php
Views: 1990 Kathleen Sweetser

12:07
Views: 20497 Elizabeth Lynch

11:05
Recorded with http://screencast-o-matic.com
Views: 40520 Courtney Vidacovich

08:11
A discussion of Type I errors, Type II errors, their probabilities of occurring (alpha and beta), and the power of a hypothesis test.
Views: 259728 jbstatistics

16:07
This video explains how to calculate a priori and post hoc power calculations for correlations and t-tests using G*Power. G*Power download: http://www.gpower.hhu.de/en.html Howell reference: Howell, D. C. (2012). Statistical methods for psychology. Cengage Learning.
Views: 23681 Social Science Club

12:33
This lecture discusses utilizing power analysis in experimental design.
Views: 4630 Matthew Novak

05:28
Video providing an overview of how power is determined and how it relates to sample size.
Views: 48372 Terry Shaneyfelt

11:32
An example of calculating power and the probability of a Type II error (beta), in the context of a Z test for one mean. Much of the underlying logic holds for other types of tests as well. If you are looking for an example involving a two-tailed test, I have a video with an example of calculating power and the probability of a Type II error for a two-tailed Z test at http://youtu.be/NbeHZp23ubs.
Views: 307237 jbstatistics

15:46
This video will go over three issues that can arise when scientific studies have low statistical power. All materials shown in the video, as well as the content from our other videos, can be found here: https://osf.io/7gqsi/

08:10
To view a playlist and download materials shown in this eCourse, visit the course page at: http://www.jmp.com/en_us/academic/ssms.html
Views: 13843 ProfessorParris

12:13
How to calculate beta and power. This video attempts to simply explain the concept of statistical power. The first half of the video works with some given information (Ho/Ha, n, sigma, and alpha). At the 8 minute mark, I introduce the alternative mu of 20.5 (a hypothetical value, as are most alternative values of mu, to calculate the power of the test against this alternative). This is a "two sided, greater than" example. A "one sided, less than" example can be found here: http://www.youtube.com/watch?v=zXbSogwX8Wc Stoney Pryor
Views: 83788 StoneyP94

05:22
Who: Dr. Daniël Lakens Assistant Professor of Psychology Eindhoven University of Technology Questions: - What is "power"? - Why is it important to consider power and sample size before designing a study? - What effect does a lack of consideration of power and sample size have on knowledge in the field?

05:31
What is a power analysis and when should we do it when scheduling a clinic study or other experimental design? Do we always need one?
Views: 7359 FredDoreyStatistics

04:06
Short presentation on power analysis
Views: 1320 Romaine Johnson

06:48
This video demonstrates how to calculate power and the probability of Type II error (beta error) in SPSS. Observed power and its relationship to beta error probability are reviewed.
Views: 22552 Dr. Todd Grande

14:12
How to calculate sample sizes for t-tests (independent and paired samples) Download G*Power here: http://www.gpower.hhu.de/en.html Like, Comment, and Subscribe for more content like this

13:40
An example of calculating power and the probability of a Type II error (beta), in the context of a two-tailed Z test for one mean. Much of the underlying logic holds for other types of tests as well. I have a related video with a one-tailed Z test example available at http://youtu.be/BJZpx7Mdde4.
Views: 140825 jbstatistics

05:25
This video illustrates how to calculate power for a Pearson correlation coefficient. We look at the sample size required to get a desired power level (.80 is generally recommended) for for different values of Pearson r. G Power

05:48
This video tutorial shows you how to calculate the power of a one-sample and two-sample tests on means. The code will soon be on my blog page. Here is the link to the page with the syntax. http://threestandarddeviationsaway.blogspot.com/p/calculating-power-in-r.html
Views: 18144 Ed Boone

05:17
Using G*Power to Determine Sample Size
Views: 43317 Dr. Ubirathan Miranda

08:28
Views: 27726 Arthur Bangert

14:40
Examples for conducting a priori and post hoc power analyses in G*Power for paired-samples and independent-samples t-tests.
Views: 45774 miamipsych293

06:59
This video will introduce how to calculate statistical power in R using the pwr package. All materials shown in the video, as well as content from our other videos, can be found here: https://osf.io/7gqsi/

15:54
SKIP AHEAD: 0:39 – Null Hypothesis Definition 1:42 – Alternative Hypothesis Definition 3:12 – Type 1 Error (Type I Error) 4:16 – Type 2 Error (Type II Error) 4:43 – Power and beta 6:33 – p-Value 8:39 – Alpha and statistical significance 14:15 – Statistical hypothesis testing (t-test, ANOVA & Chi Squared) For the text of this video click here http://www.stomponstep1.com/p-value-null-hypothesis-type-1-error-statistical-significance/ For my video on Confidence Intervals click here http://www.stomponstep1.com/confidence-interval-interpretation-95-confidence-interval-90-99/
Views: 487238 Stomp On Step 1

02:46
A video on how to calculate the sample size. Includes discussion on how the standard deviation impacts sample size too. Like us on: http://www.facebook.com/PartyMoreStudyLess Related Video How to calculate Samples Size Proportions http://youtu.be/LGFqxJdk20o
Views: 312054 statisticsfun

01:07:37
A central concern in social science research is statistical power, or the ability of a given analysis to reliably detect the presence or absence of any effect(s). Without enough participants, an effect may in fact exist, but the researcher may be unable to detect it and falsely conclude that it does not exist. Conversely, with too many participants, clinically insignificant effects may reach statistical significance. Using examples, this presentation focuses on how to use G*Power software to determine how many participants are needed to reliably detect—or safely reject—the existence of effects in the real world. Attendees should download G*Power at this site before joining the meeting: http://www.gpower.hhu.de/en.html Chicago School students can download the presentation slides here: https://tcsedsystem-my.sharepoint.com/personal/kglazek_thechicagoschool_edu/_layouts/15/guestaccess.aspx?guestaccesstoken=q6HTQO94Nfd%2bON2JM1Wdbpa76j8f2XtTMrVuHNgZdXQ%3d&docid=2_1c127379ce4ed4998a93aea43d440e737&rev=1

19:59
Power and Error Calculations in Hypothesis Testing and Statistics with Examples: What is Power(sensitivity) in Statistics and How to Calculate it? What factors influence errors in hypothesis testing and power of the test? How can we increase power of a test in research and statistics? 👉🏼 Errors and Power in Statistics Video: ( https://youtu.be/OYbc3uKpGmg ); Sensitivity, Specificity, Positive and Negative Predictive Values Video (https://youtu.be/eeM7KPRNlSs) 👍🏼Best Statistics & R Programming Language Tutorials: ( https://goo.gl/4vDQzT ) ►► Like to support us? You can Donate (https://bit.ly/2CWxnP2), Share our Videos, Leave us a Comment and Give us a Like! Either way We Thank You! In this statistics video lecture we learn about statistical power of a hypothesis test and type II error in statistics and in research.This tutorial covers the concept of power in statistics, how statistical power can be calculated, and the factors that affect power. Here, we explore more in detail how the Power is related to alpha, the sample size (n), and the difference we wish to detect. The goal is to use this as a foundation for understanding the concept of power, and the factors that affect it. While power calculations can become quite complicated very quickly, the underlying concept is always the same. This video should lay a foundation for understanding power as a concept. Some of these terminology can be confusing at first. when "rejecting a null hypothesis", this is referred to as a "positive test result". "failing to reject the null" is a "negative test result" (much like disease testing, null is that you don’t have disease, alternative is that you do have the disease, and testing positive means we reject the null and conclude that you have the disease, and vice versa). A Type I error is when we reject the null when in reality it is true. when we reject the null this is a "positive test result" and if in reality this is incorrect, it is a "false positive". ►► Watch More: ► Statistics Course for Data Science https://bit.ly/2SQOxDH ►R Course for Beginners: https://bit.ly/1A1Pixc ►Getting Started with R using R Studio (Series 1): https://bit.ly/2PkTneg ►Graphs and Descriptive Statistics in R using R Studio (Series 2): https://bit.ly/2PkTneg ►Probability distributions in R using R Studio (Series 3): https://bit.ly/2AT3wpI ►Bivariate analysis in R using R Studio (Series 4): https://bit.ly/2SXvcRi ►Linear Regression in R using R Studio (Series 5): https://bit.ly/1iytAtm ►ANOVA Statistics and ANOVA with R using R Studio : https://bit.ly/2zBwjgL ►Hypothesis Testing Videos: https://bit.ly/2Ff3J9e ►Linear Regression Statistics and Linear Regression with R : https://bit.ly/2z8fXg1 Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook: https://goo.gl/qYQavS Twitter: https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some statistics courses at the University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials ), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn! #statistics #rprogramming

01:01:10
Dale W. Usner, Ph.D., President at SDC, explains the basics of statistical power for non-statisticians, highlighting what you need to know about statistical power, how it affects your clinical trial, and what to ask for from your statistician.

05:03
I address the issue of what sample size you need to conduct a multiple regression analysis.
Views: 17862 how2stats

01:26
This tutorial demonstrates how to calculate statistical power using SPSS.
Views: 117982 Amanda Rockinson-Szapkiw

23:30
Illustrating the use of the Excel simulation, and PiFace, to do power analysis, as discussed in Tutorial 1. Also includes comments on software, sample size and effect size.
Views: 4570 Keith McGuinness

06:56
Shows how to conduct a statistical power analysis, as well as determine minimum sample size requirements, in a structural equation modeling (SEM) analysis using the software WarpPLS.
Views: 1007 scriptwarp

07:32
Views: 6913 Elizabeth Lynch

21:07
Views: 264 Vidya-mitra

22:10
Statistical Power is a conditional probability of a correct decision given that there truly is an effect. Power is affected by the sample size, the effect size, the alpha, and the variance.
Views: 3944 Frank Rust

05:52
Learn what a power analysis is and how to run one using G*Power Download G*Power: http://www.gpower.hhu.de/en.html For questions: [email protected]
Views: 1711 The Psychology Series

05:55
This video tutorial shows how to calculate the sample size for tests on means using the R statistical software. The R code used in the video is available on the following blog page. http://threestandarddeviationsaway.blogspot.com/p/calculating-sample-size-in-r-means.html
Views: 24589 Ed Boone

08:51
In this video we will discus the concept of statistical power and how it relates to Type I and Type II errors. NOTE: These videos were originally part of a special series of lectures derived from the material in crp241. There are references to other modules and to a program called statcrunch that was used for this series; don't worry about either. The videos stand on their own and cover topics relevant to the discussion and activities in crp241.
Views: 4541 Steve Grambow