This 7-minute video lesson compares Z-statistics and T-statistics. [Statistics playlist: Lesson 49 of 85]
Paul Anderson's video playlist of videos that can be used in a Statistics and Graphing class
The goal of this repository is to index and host short videos that can be used to supplement the teaching of introductory statistics concepts. The purpose of these videos is to show students examples of statistical concepts being used in real research, to build off of foundational understanding of the concept they were introduced to in class. Let's show students real people, doing real research, and using real baby statistics to solve science! If you are interested to contribute a video to this page, please read the wiki, which explains what is needed in more depth. If you are still interested to contribute at that point, please request access as a contributor for the specific component(s) you would like to contribute to. If you would like to contribute a video for a topic that is not listed as a component, please contact JK Flake.
Students will explore the overarching question, is the internet trustworthy?, while expanding their knowledge of statistics and comparing data sets. They will compare two data sets as well as determine the accuracy or bias of data representations shown on the internet. Students will then have the opportunity to apply their knowledge while creating their own visual representations for data they personally collected regarding the trustworthiness of the internet. The module concludes with a peer showcase and the post-assessment.
Statistical data have a tendency to cluster around some central point.
How do we determine this point?
Is there just one way of doing it or more than one?
Different ways of displaying data: boxplots, histograms and distributions.
Things you need to know before looking at the statistics courses here.
One of the most common statistical distributions is the normal distribution. What does it tell us and how do we use it?
A standard way of measuring statistical variability: standard deviation and the associated concepts of variance and degrees of freedom.
Understanding the summation sign: what does it do … why does it exist?
Statistical data vary: range and inter-quartile range measure this. Are they good measures?
This 8-minute video lesson takes some problems from CK12.org to provide Z-score practice. [Statistics playlist: Lesson 31 of 85]
This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications. The goal is to understand the role of mathematics in the research and development of efficient statistical methods.
Provides students with the basic tools for analyzing experimental data, properly interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics organized around three key theories: Probability, statistical, and the linear model. Probability theory covers axioms of probability, discrete and continuous probability models, law of large numbers, and the Central Limit Theorem. Statistical theory covers estimation, likelihood theory, Bayesian methods, bootstrap and other Monte Carlo methods, as well as hypothesis testing, confidence intervals, elementary design of experiments principles and goodness-of-fit. The linear model theory covers the simple regression model and the analysis of variance. Places equal emphasis on theory, data analyses, and simulation studies.
About Stats of DOOM
Support Statistics of DOOM! This page and the YouTube channel to help people learn statistics by including step-by-step instructions for SPSS, R, Excel, and other programs. Demonstrations are provided including power, data screening, analysis, write up tips, effect sizes, and graphs. Help guides and course materials are also provided!
When I originally started posting my videos on YouTube, I never really thought people would be interested in them - minus a few overachieving students. I am glad that I've been able to help so many folks! I have taught many statistics courses - you can view full classes by using the Learn tab in the top right. I have also taught cognitive and language courses, some with coding (see the NLP and Language Modeling courses), and some without (see Other Courses). I hope this website provides structure to all my materials for you to use for yourself or your classroom.
Each page has an example syllabus, video lectures laid out with that syllabus (if I have them!), and links to the appropriate materials. Any broken links can be reported by sending me an email (linked at the bottom). Stats Tools was designed for learning statistics, which morphed into learning coding, open science, statistics, and more! Recommendations, comments, and other questions are welcome with the general suggestion to post on the specific video or page you have a question on. I do my best to answer, but also work a full-time job.
These resources wouldn't be possible without the help of many fantastic people over the years including:
All the Help Desk TAs: Rachel E. Monroe, Marshall Beauchamp, Louis Oberdiear, Simone Donaldson, Kim Koch, Jessica Willis, Samantha Hunter, Flora Forbes, Tabatha Hopke
Research colleagues: K.D. Valentine, John E. Scofield, Jeff Pavlacic
And more! Pages with specific content made by others are noted on that page.
This webinar will introduce the integration of JASP Statistical Software (https://jasp-stats.org/) with the Open Science Framework (OSF; https://osf.io). The OSF is a free, open source web application built to help researchers manage their workflows. The OSF is part collaboration tool, part version control software, and part data archive. The OSF connects to popular tools researchers already use, like Dropbox, Box, Github, Mendeley, and now is integrated with JASP, to streamline workflows and increase efficiency.
StatsCasts are narrated screen video recordings of explanations of statistical concepts. They are produced by Swinburne University of Technology, the University of the Sunshine Coast, and the University of Southern Queensland.
They are part of an ongoing collaborative research project to develop high quality resources and investigate the effectiveness of StatsCasts to support statistics learning.
They are targeted at prerequisite to first year level, in a range of subjects such as: Engineering, Sciences, Health Sciences and Business.
A resource for learning about probability and statistics. The text is motivated by real data and is integrated with interactive features such as applets, videos, and example prompts.
Video lectures covering all topics in a psychology introductory statistics course.
I have designed and presented the content within StatsforMedics specifically for use by undergraduate medical students who are considering use of statistics for short-term research projects. However, this is with the understanding that students from allied health sciences may also benefit from engaging with the site and its sister site, Statistics CALs. Also, I am currently exploring use of selected content for outreach work in pre-university sectors.