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Research Methods in Psychology (New Zealand edition)
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CC BY-NC-SA
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This textbook is an adaptation of the Research Methods in Psychology that is available on this site in US and Canadian editions. This New Zealand edition is an adaptation to the New Zealand context. The main changes are in Chapters 1 and 3 and the spelling, grammar, and terminology are changed throughout. This textbook is adopted at the University of Waikato in our 200-level research methods in psychology class.

Subject:
Psychology
Social Science
Material Type:
Textbook
Author:
Paul C. Price
Rajiv S. Jhangiani
Date Added:
04/27/2020
Statistical Inference For Everyone
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CC BY-SA
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This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester of such a course. It is freely available under the Creative Commons License, and includes a software library in Python for making some of the calculations and visualizations easier.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Author:
Brian Blais
Date Added:
04/27/2020
Statistical Thinking for the 21st Century
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CC BY-NC
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Statistical thinking is a way of understanding a complex world by describing it in relatively simple terms that nonetheless capture essential aspects of its structure, and that also provide us some idea of how uncertain we are about our knowledge. The foundations of statistical thinking come primarily from mathematics and statistics, but also from computer science, psychology, and other fields of study.

Subject:
Mathematics
Statistics and Probability
Material Type:
Textbook
Author:
Russel A. Poldrack
Date Added:
04/27/2020
Statistics Course Content
Unrestricted Use
CC BY
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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:
04/17/2018
Statistics Course Content, Sampling Methods, Producing Data – Sampling Methods
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CC BY-NC
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Producing Data – Sampling MethodsIn this module we will explore the different sampling methods to obtain representative samples from a population. We also learn about the relative advantages and disadvantages of each method. Learning Objectives:Reasons for samplingRandom Vs. Non-Random SamplesSampling Bias and VariabilityRandom Sampling Methods – Simple, Stratified, Systematic, Cluster and Multistage random samplesNon-Random Sampling Methods – Voluntary Response and Convenience samplingSample surveys, sampling errorsBest method of random samplingSampling distributions

Subject:
Statistics and Probability
Material Type:
Module
Date Added:
07/02/2018
Statistics Course Content, Technology, Excel and Google Spreadsheets
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CC BY-NC
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This module contains Excel and Google Spreadsheets for all statistical procedures used in an Intro Stats course. The spreadsheets are self-explanatory. Students insert data in the indicated areas. Spreadsheets are designed to automatically complete all calculations and show the results.One Variable Statistics Frequency DistributionDiscrete Probability DistributionNormal DistributionConfidence IntervalsTest of HypothesisLinear RegressionIndependence

Subject:
Statistics and Probability
Material Type:
Module
Date Added:
07/03/2018
Think Stats: Probability and Statistics for Programmers
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CC BY-NC
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Think Stats is an introduction to Probability and Statistics for Python programmers.

*Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
*If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.

Subject:
Applied Science
Computer Science
Mathematics
Statistics and Probability
Material Type:
Textbook
Provider:
Green Tea Press
Author:
Allen Downey
Date Added:
01/01/2014