This 7-minute video lesson provides an introduction to the idea that one can find a line that minimizes the squared distances to the points. [Statistics playlist: Lesson 62 of 85]
This 15-minute video lesson looks at the Standard Error of the Mean (a.k.a. the standard deviation of the sampling distribution of the sample mean!). [Statistics playlist: Lesson 38 of 85]
This 12-minute video lesson looks at the T-Statistic Confidence Interval (for small sample sizes). [Statistics playlist: Lesson 52 of 85]
This Open Educational Resource (OER) carries a significant responsibility by presenting statistics through an equity lens. The metaphor of a lens is used intentionally–as the glasses one wears can have a profound effect on what one sees. The book encourages further inspection of the ways in which data is collected, interpreted, and analyzed on a variety of social justice issues, such as health disparities, hunger and food insecurity, homelessness, behavioral health (mental health and substance use), and incarceration of males of color. It also attempts to reveal how the misuse of data can reinforce inequities, for example, by stigmatizing people and labeling neighborhoods as high poverty, violent, and having poor educational opportunities. Whether an intended or unintended consequence, irresponsible data use can contribute to racist impressions of people and communities.
This 3-minute video lesson discusses Type I Errors. [Statistics playlist: Lesson 50 of 85]
This textbook follows the GAISE Standards (GAISE recommendations. (2014, January
05). To this end, students are asked to interpret the results of their calculations. I incorporated the use of technology (R Studio) for most calculations. Because of that you will not find the book using any of the computational formulas for standard deviations or correlation and regression since I prefer students understand the concept of these quantities. Also, because of utilizing technology you will not
find the standard normal table, Student’s t-table, binomial table, chi-square distribution table, and F-distribution table in the book. Another difference between this book and other statistics books is the order of hypothesis testing and confidence intervals. Most books present confidence intervals first and then hypothesis tests. This book presents hypothesis testing first and then confidence intervals is more understandable for students. Lastly, the use of the z-test is deemphasized. Two samples should be emphasized over one sample test. Lastly, to aid student understanding and interest, most of the homework and examples utilize real data with multiple variables. The beauty of multiple variables, is that you can ask the students to investigate different analysis with different variables. This way students can work with data and come up with connections
of asking questions and using data to answer the questions. Again, I hope you find this book useful for your introductory statistics class.
From the website: "Statistics With Technology, Second Edition, is an introductory statistics textbook. It uses the TI-83/84 calculator and R, an open source statistical software, for all calculations. Other technology can also be used besides the TI-83/84 calculator and the software R, but these are the ones that are presented in the text. This book presents probability and statistics from a more conceptual approach, and focuses less on computation. Analysis and interpretation of data is more important than how to compute basic statistical values.
License: Creative Commons Attribution Sharealike. This license is considered to be some to be the most open license. It allows reuse, remixing, and distribution (including commercial), but requires any remixes use the same license as the original. This limits where the content can be remixed into, but on the other hand ensures that no-one can remix the content then put the remix under a more restrictive license.
Formats:
DOC. A DOC file can be opened using Microsoft Word or OpenOffice.org. It is an editable format
PDF. A Portable Document Format (PDF) file is can be opened using the free Acrobat Reader. It is not an editable format.
Openness Rating (0-4): 3.5"
This 11-minute video lesson discusses variance of differences of random variables. [Statistics playlist: Lesson 54 of 85]
This 12-minute video lesson explains variance of a population. [Statistics playlist: Lesson 13 of 85]
TED Studies, created in collaboration with Wiley, are curated video collections supplemented by rich educational materials for students, educators and self-guided learners. In Visualizing Data, TED speakers shake up statistics with elegant, dynamic representations that make mountains of data comprehensible and even exciting. Learn how to visualize data and present complicated statistics in elegant and captivating ways. Relevant areas of interest, study and coursework include: information design, demography, statistical literacy, economics, sociology, media studies, linguistics, meteorology and computer science.
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
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.
This 8-minute video lesson takes some problems from CK12.org to provide Z-score practice. [Statistics playlist: Lesson 31 of 85]
cological data pose many challenges to statistical inference. Most data come from observational studies rather than designed experiments; observational units are frequently sampled repeatedly over time, resulting in multiple, non-independent measurements; response data are often binary (e.g., presence-absence data) or non-negative integers (e.g., counts), and therefore, the data do not fit the standard assumptions of linear regression (Normality, independence, and constant variance). This book will familiarize readers with modern statistical methods that address these complexities using both frequentist and Bayesian frameworks.
An Open Access Resource with Self-Tests and Illustrative Examples
Short Description:
This book aims to help you understand and navigate statistical concepts and the main types of statistical analyses essential for research students.
Word Count: 21748
ISBN: 978-0-6453261-0-9
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
Word Count: 145555
(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)
As we near the end of the series, we're going look at how statistics impacts our lives. Today, we're going to discuss how statistics is often used and misused in the courtroom. We're going to focus on three stories in which three huge statistical errors were made: the handwriting analysis of French officer Alfred Dreyfus in 1894, the murder charges of mother Sally Clark in 1998, and the expulsion of student Jonathan Dorfman from UC San Diego in 2011.
This unit is a multidisciplinary unit created for a high school math classroom, designed to combine statistics and hydrology. In this unit, students will learn about the water cycle and water budgets within the watershed. The unit starts with learning about basic budgeting in a watershed, comparable to financial budgeting, and expands to creating linear regressions based on the relationship between precipitation, discharge, and evapotranspiration in a watershed system. Students will be able to synthesize the information they learn about the watershed to learn about topics such as graphing points, lines, creating scatterplots, and creating linear regressions for the line of best fit. By teaching statistics through the lens of the watershed, the primary objective is to facilitate active, engaged learners who understand how math can be usefully applied to various contexts in the world around us while gaining a deeper appreciation for the water resources on Earth.
This was designed for a Geometry classroom, but could be modified for Pre-Algebra- Statistics based on student needs and interest level.
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.