Updating search results...

33 Results

View
Selected filters:
• correlation
Conditional Remix & Share Permitted
CC BY-SA
Rating
0.0 stars

By the end of this section, you will be able to:Explain what a correlation coefficient tells us about the relationship between variablesRecognize that correlation does not indicate a cause-and-effect relationship between variablesDiscuss our tendency to look for relationships between variables that do not really existExplain random sampling and assignment of participants into experimental and control groupsDiscuss how experimenter or participant bias could affect the results of an experimentIdentify independent and dependent variables

Subject:
Psychology
Social Science
Material Type:
Module
Author:
Melinda Boland
01/12/2018
Unrestricted Use
Public Domain
Rating
0.0 stars

Students will use state and regional unemployment data for various education levels to create scatter plots and calculate correlation coefficients. Students will then compare scatter plots with different strengths of linear relationships and will determine the impact of any influential points on the correlation coefficient.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
U.S. Census Bureau
Provider Set:
Statistics in Schools
10/15/2019
Read the Fine Print
Educational Use
Rating
0.0 stars

Students act as R&D entrepreneurs, learning ways to research variables affecting the market of their proposed (hypothetical) products. They learn how to obtain numeric data using a variety of Internet tools and resources, sort and analyze the data using Excel and other software, and discover patterns and relationships that influence and guide decisions related to launching their products. First, student pairs research and collect pertinent consumer data, importing the data into spreadsheets. Then they clean, organize, chart and analyze the data to inform their product production and marketing plans. They calculate related statistics and gain proficiency in obtaining and finding relationships between variables, which is important in the work of engineers as well as for general technical literacy and decision-making. They summarize their work by suggesting product launch strategies and reporting their findings and conclusions in class presentations. A finding data tips handout, project/presentation grading rubric and alternative self-guided activity worksheet are provided. This activity is ideal for a high school statistics class.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
TeachEngineering
Provider Set:
Activities
Author:
Tom Falcone
05/03/2017
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
Anderson-Cook, C.
C. Anderson-Cook
Dorai-Raj, S.
Robinson, T.
S. Dorai-Raj
T. Robinson
02/16/2011
Conditional Remix & Share Permitted
CC BY-SA
Rating
0.0 stars

This example walks student through process step by step.

Subject:
Statistics and Probability
Material Type:
Module
Author:
Laura Ralston
05/24/2017
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

Understanding why correlation does not imply causality (even though many in the press and some researchers often imply otherwise).

Subject:
Mathematics
Statistics and Probability
Material Type:
Lesson
Provider:
Author:
Salman Khan
12/27/2017
Only Sharing Permitted
CC BY-NC-ND
Rating
0.0 stars

An introduction and examples of how to use Correlation and Simple Linear Regression. Explaining concepts as coefficient of correlation, dependent variables, independent variables and the straight line equation and residuals.

Subject:
Applied Science
Health, Medicine and Nursing
Mathematics
Statistics and Probability
Material Type:
Lecture
Provider:
Umeå University
Provider Set:
Quantitative Research Methods
Author:
Marie Lindqvist
Associate professor in epidemiology and biostatistics
11/01/2014
Unrestricted Use
CC BY
Rating
0.0 stars

With your mouse, drag data points and their error bars, and watch the best-fit polynomial curve update instantly. You choose the type of fit: linear, quadratic, cubic, or quartic. The reduced chi-square statistic shows you when the fit is good. Or you can try to find the best fit by manually adjusting fit parameters.

Subject:
Mathematics
Material Type:
Simulation
Provider:
University of Colorado Boulder
Provider Set:
PhET Interactive Simulations
Author:
Michael Dubson
Trish Loeblein
08/01/2008
Only Sharing Permitted
CC BY-NC-ND
Rating
0.0 stars

This lesson unit is intended to help teachers assess how well students understand the notion of correlation. In particular this unit aims to identify and help students who have difficulty in: understanding correlation as the degree of fit between two variables; making a mathematical model of a situation; testing and improving the model; communicating their reasoning clearly; and evaluating alternative models of the situation.

Subject:
Mathematics
Material Type:
Assessment
Lesson Plan
Provider:
Shell Center for Mathematical Education
Provider Set:
Mathematics Assessment Project (MAP)
04/26/2013
Unrestricted Use
Public Domain
Rating
0.0 stars

Students will develop, justify, and evaluate conjectures about the relationship between two quantitative variables over time in the United States: the median age (in years) when women first marry and the percentage of women aged 25–34 with a bachelor’s degree or higher. Students will write a regression equation for the data, interpret in context the linear model’s slope and y-intercept, and find the correlation coefficient (r), assessing the strength of the linear relationship and whether a significant relationship exists between the variables. Students will then summarize their conclusions and consider whether correlation implies causation.

Subject:
Mathematics
Statistics and Probability
Material Type:
Activity/Lab
Provider:
U.S. Census Bureau
Provider Set:
Statistics in Schools
10/15/2019
Only Sharing Permitted
CC BY-NC-ND
Rating
0.0 stars

These resources were created to compliment our undergraduate statistics lab manual, Applied Data Analysis in Psychology: Exploring Diversity with Statistics, published by Kendall Hunt publishing company. Like our lab manual, these JASP walk-through guides meaningfully and purposefully integrate and highlight diversity research to teach students how to analyze data in an open-source statistical program. The data sets utilized in these guides are from open-access databases (e.g., Pew Research Center, PLoS One, ICPSR, and more). Guides with step-by-step instructions, including annotated images and examples of how to report findings in APA format, are included for the following statistical tests: independent samples t test, paired samples t test, one-way ANOVA, two factor ANOVA, chi-square test, Pearson correlation, simple regression, and multiple regression.

Subject:
Education
Mathematics
Psychology
Social Science
Statistics and Probability
Material Type:
Activity/Lab
Data Set
Student Guide
Teaching/Learning Strategy
Provider:
University of Tennessee at Chattanooga
Author:
Ashlyn Moraine
Asia Palmer
Hannah Osborn
Kelsey Humphrey
Kendra Scott
Kristen J. Black
Ruth V. Walker
01/13/2022
Only Sharing Permitted
CC BY-ND
Rating
0.0 stars

This paper serves as an exploration into some of the ways in which organizations can promote, capture, share, and manage the valuable knowledge of their employees. The problem is that employees typically do not share valuable information, skills, or expertise with other employees or with the entire organization. The author uses research as well as her graduate studies in the field of Human Resource Development (HRD) and professional career experiences as an instructor and training and development consultant to make a correlation between the informal workplace learning experiences that exist in the workplace and the need to promote, capture, and support them so they can be shared throughout the organization. This process, referred to as knowledge sharing, is the exchange of information, skills, or expertise among employees of an organization that forms a valuable intangible asset and is dependent upon an organization culture that includes knowledge sharing, especially the sharing of the knowledge and skills that are acquired through informal workplace learning; performance support to promote informal workplace learning; and knowledge management to transform valuable informal workplace learning into knowledge that is promoted, captured, and shared throughout the organization.

Subject:
Career and Technical Education
English Language Arts
Management
Material Type:
Case Study
Lecture
Author:
Caruso Shirley J
02/22/2022
Unrestricted Use
CC BY
Rating
0.0 stars

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Critically ill COVID-19 patients under invasive mechanical ventilation (IMV) are at greatly increased risk of death compared to the general population. While some drivers of COVID-19 disease progression, such as inflammation and hypercoagulability, have been identified, they do not completely explain the mortality of critically ill COVID-19 patients, making a search for overlooked factors necessary. A recent study examined the virome of tracheal aspirates from 25 COVID-19 patients under IMV. These samples were compared to tracheal aspirates from non-COVID patients and nasopharyngeal swabs from individuals with mild COVID-19. Critically ill COVID-19 patients had elevated expression of human endogenous retrovirus K (HERV-K), and elevated HERV-K expression in tracheal aspirate and plasma was associated with early mortality in those same patients. Among deceased patients, HERV-K expression was associated with IL-17-related inflammation, monocyte activation, and increased consumption of clotting factors..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Provider:
Research Square
Provider Set:
Video Bytes
05/18/2022
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.
Visit the Seung Lab Web site.

Subject:
Applied Science
Biology
Engineering
Life Science
Physical Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Seung, Sebastian
02/01/2004
Unrestricted Use
CC BY
Rating
0.0 stars

Introduction to Sociology 2e adheres to the scope and sequence of a typical, one-semester introductory sociology course. It offers comprehensive coverage of core concepts, foundational scholars, and emerging theories, which are supported by a wealth of engaging learning materials. The textbook presents detailed section reviews with rich questions, discussions that help students apply their knowledge, and features that draw learners into the discipline in meaningful ways. The second edition retains the book’s conceptual organization, aligning to most courses, and has been significantly updated to reflect the latest research and provide examples most relevant to today’s students. In order to help instructors transition to the revised version, the 2e changes are described within the preface.

Subject:
Social Science
Sociology
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
02/01/2012
Unrestricted Use
CC BY
Rating
0.0 stars

Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysisUnderstand why different topics are better suited to different research approaches

Subject:
Social Science
Sociology
Material Type:
Module
11/15/2016
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

This is a three-credit course which covers topics that enhance the students’ problem solving abilities, knowledge of the basic principles of probability/statistics, and guides students to master critical thinking/logic skills, geometric principles, personal finance skills. This course requires that students apply their knowledge to real-world problems. A TI-84 or comparable calculator is required. The course has four main units: Thinking Algebraically, Thinking Logically and Geometrically, Thinking Statistically, and Making Connections. This course is paired with a course in MyOpenMath which contains the instructor materials (including answer keys) and online homework system with immediate feedback. All course materials are licensed by CC-BY-SA unless otherwise noted.

07/08/2021
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars
Rating
0.0 stars
Conditional Remix & Share Permitted
CC BY-NC-SA
Rating
0.0 stars

Topics List for this Lesson: Sampling, Frequency Distributions, and GraphsMeasures of CenterMeasures of VarianceNormal Distributions and Problem SolvingZ-Scores and Unusual ValuesEmpirical Rule and Central Limit TheoremScatterplots, Correlation, and Regression

Subject:
Mathematics
Material Type:
Full Course
Author:
Jillian Miller
Megan Simmons
Stefanie Holmes
Jessica Chambers