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Psychology
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CC BY
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Psychology is designed to meet scope and sequence requirements for the single-semester introduction to psychology course. The book offers a comprehensive treatment of core concepts, grounded in both classic studies and current and emerging research. The text also includes coverage of the DSM-5 in examinations of psychological disorders. Psychology incorporates discussions that reflect the diversity within the discipline, as well as the diversity of cultures and communities across the globe.Senior Contributing AuthorsRose M. Spielman, Formerly of Quinnipiac UniversityContributing AuthorsKathryn Dumper, Bainbridge State CollegeWilliam Jenkins, Mercer UniversityArlene Lacombe, Saint Joseph's UniversityMarilyn Lovett, Livingstone CollegeMarion Perlmutter, University of Michigan

Subject:
Psychology
Social Science
Material Type:
Full Course
Provider:
Rice University
Provider Set:
OpenStax College
Date Added:
10/19/2022
Statistics Course Content
Conditional Remix & Share Permitted
CC BY-NC
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Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.Team LeadKameswarrao Casukhela                     Ohio State University – LimaContent ContributorsEmily Dennett                                       Central Ohio Technical CollegeSara Rollo                                            North Central State CollegeNicholas Shay                                      Central Ohio Technical CollegeChan Siriphokha                                   Clark State Community CollegeLibrarianJoy Gao                                                Ohio Wesleyan UniversityReview TeamAlice Taylor                                           University of Rio GrandeJim Cottrill                                             Ohio Dominican University

Subject:
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
Ohio Open Ed Collaborative
Date Added:
11/05/2020
Statistics Course Content, Discrete Random Variables, Binomial Distribution, Discrete Random Variable, Binomial Distribution
Conditional Remix & Share Permitted
CC BY-NC
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In this module we will learn about discrete random variables, their distributions and properties. Of specific interest would be a binomial random variable, its distribution and applications.Learning Objectives:Discrete random variable, distribution, mean and standard deviationBinomial random variable and its distributionTextbook Material -  Chapter 4 – Probability Topics – Pages 239 - 257Suggested Homework:Discrete Random Variable - 69, 70, 74, 75, 76, 78, 96, 102Binomial Distribution – Odds 88 - 111  

Subject:
Statistics and Probability
Material Type:
Module
Author:
Ohio Open Ed Collaborative
Date Added:
11/05/2020
Statistics Course Content, Numerical Descriptions of Data on Single Variable, Numerical Summary of Data
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CC BY-NC
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A data set is a listing of variables and their observed values on individuals or objects of study. In this topic we will learn about numerical summaries of data on a single variable and learn how to use them to describe data distribution and determine unusual values in the data. The type of numerical summaries to use depend on the data. We will also learn about boxplots.Learning Objectives:Understand which numerical summaries must be used to represent dataBe able to compute and interpret them. Also, know their properties and relative advantages and disadvantages. Further, use these measures to describe distributions, compare values from distributions, detect unusual values in the data, etc.For categorical data use counts and proportions to describe categoriesFor quantitative data useMeasures of Center – Mean, Median, ModeMeasure of Spread – Range, Interquartile Range (IQR), Variance and Standard DeviationMeasures of Location – Minimum, Maximum, Quartiles and PercentilesLearn to distinguish between different types of distributions for quantitative data – symmetric, skewed, bell-shaped, multimodal distributionsLearn about Empirical Rule for bell-shaped distributionsUse z-scores to compare values and detect unusual valuesMake boxplot of dataTextbook Material: Chapter 2 – Descriptive Statistics – Pages 88 - 122Suggested HomeworkChapter 2 - Descriptive Statistics – 29, 31, 32, 43, 57, 60, 69, 71, 82, 84, 86, 88, 89, 104, 106, 108, 109, 115, 119

Subject:
Statistics and Probability
Material Type:
Module
Author:
Ohio Open Ed Collaborative
Date Added:
11/05/2020