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Measures of Correlation and Contingency

Mike Stadler, PhD and Peter Cardamone

This course provides a comprehensive exploration of statistical relationships, focusing on the principles and applications of correlation and contingency tables. Students will learn to identify appropriate scenarios for using correlation, understand its logic, and describe its direction and strength. The course also covers the use of contingency tables, teaching students to recognize patterns of association within them.

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What's inside

Syllabus

Learn With PsycLearn Essentials
This module introduces you to your PsycLearn Essentials course. Find out what’s included in this course and how to navigate the modules and lessons. You’ll also learn valuable study tips for successful learning.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Offers APA student resources, which may be valuable for students pursuing coursework and career goals in psychology
Explores statistical relationships, which are fundamental for understanding research findings and data analysis in psychology
Covers contingency table analysis, which is essential for examining relationships between categorical variables in psychological research
Presented by the American Psychological Association, a leading organization in the field of psychology

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Reviews summary

Statistical relationships in psychology

According to learners, this course provides a solid introduction to measures of correlation and contingency, particularly relevant for students of psychology. Many found the explanations clear and easy to follow, making complex statistical concepts accessible. Reviewers frequently highlighted the course's focus on the practical application of these methods. While some found the content slightly basic if they had prior statistical knowledge, for many, it served as a helpful refresher or a strong foundational course. The inclusion of APA resources was seen as a valuable addition for psychology students.
Provided useful additional resources from APA.
"The final module with APA student resources was a fantastic addition."
"I wasn't expecting the APA resources, but they were really valuable for career planning."
"Access to APA materials relevant to psychology students was a definite plus."
"The links and info provided by APA are super helpful beyond the course content."
Useful for beginners or those needing review.
"For someone new to statistics, this course provided a really good foundation."
"It was a perfect refresher on correlation and contingency that I needed for my research."
"If you're starting out or need to brush up on these topics, this course is great."
"I found it helpful as a stepping stone before diving into more advanced statistics."
Helped understand how to use methods in practice.
"I learned how to identify when to use correlation and contingency tables in real data."
"The course focused nicely on the practical aspects of applying these statistical tests."
"It wasn't just theory; it showed me how these concepts are used in actual research scenarios."
"Helped me feel more confident in applying these measures to data sets."
The course is highly relevant for psychology students.
"This course was perfect for understanding the statistical methods used in psychology research."
"As a psychology student, I found the content on correlation and contingency tables directly applicable to my studies."
"The APA resources at the end were a great bonus for my psychology career interests."
"It connects these statistical measures clearly to a psychology context."
Concepts were explained in an easy-to-understand way.
"The course material was very clear and easy to follow, especially the explanations of correlation."
"I appreciated how the concepts of correlation and contingency were broken down simply."
"The lectures made complex statistical ideas accessible even for someone new to the topic."
"Everything was laid out clearly, module by module, making it easy to grasp the material."
Content may be too simple for those with prior stats.
"If you already have a background in statistics, much of this course will be review and might feel a bit slow."
"I found the concepts were covered at a very introductory level."
"Someone with previous stats courses might find it a bit basic."
"It felt like a surface-level look at correlation and contingency for my prior knowledge level."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Measures of Correlation and Contingency with these activities:
Review Basic Statistics Concepts
Reinforce foundational statistical concepts like variables, distributions, and hypothesis testing to better understand correlation and contingency.
Browse courses on Basic Statistics
Show steps
  • Review definitions of variables and data types.
  • Practice calculating descriptive statistics (mean, median, mode).
  • Review the concept of statistical significance.
Review 'Statistics for the Behavioral Sciences'
Solidify understanding of statistical principles and their application in behavioral sciences.
View Essentials of Statistics for the Behavioral... on Amazon
Show steps
  • Read chapters on correlation and regression.
  • Work through practice problems related to correlation coefficients.
  • Review the assumptions underlying correlation and regression.
Calculate Correlation Coefficients
Practice calculating Pearson's r and Spearman's rho to improve proficiency in quantifying relationships between variables.
Show steps
  • Find datasets with two continuous variables.
  • Calculate Pearson's r using a statistical software package.
  • Calculate Spearman's rho for ordinal data.
  • Interpret the strength and direction of the correlations.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Create a Contingency Table Analysis Report
Reinforce understanding of contingency tables by creating a report analyzing a real-world dataset.
Browse courses on Contingency Tables
Show steps
  • Find a dataset with two categorical variables.
  • Create a contingency table using statistical software.
  • Calculate chi-square statistic and interpret the results.
  • Write a report summarizing the findings and their implications.
Review 'Discovering Statistics Using IBM SPSS Statistics'
Learn how to perform correlation and contingency analyses using SPSS.
View Discovering Statistics Using JASP on Amazon
Show steps
  • Read chapters on correlation and contingency tables in SPSS.
  • Follow the examples in the book to perform analyses on sample datasets.
  • Practice interpreting the SPSS output.
Correlation and Contingency in Research
Apply knowledge of correlation and contingency to analyze a research question using real-world data.
Browse courses on Correlation
Show steps
  • Identify a research question involving two variables.
  • Find a relevant dataset.
  • Perform appropriate correlation or contingency analysis.
  • Interpret the results and draw conclusions.
  • Write a research report summarizing the findings.
Tutor Students in Correlation and Contingency
Solidify your understanding by explaining correlation and contingency concepts to other students.
Browse courses on Correlation
Show steps
  • Offer tutoring sessions to students struggling with the material.
  • Prepare explanations and examples to illustrate key concepts.
  • Answer questions and provide feedback on practice problems.

Career center

Learners who complete Measures of Correlation and Contingency will develop knowledge and skills that may be useful to these careers:
Statistician
Statisticians develop and apply statistical theories and methods to collect, analyze, and interpret quantitative data. A statistician will regularly employ correlation and contingency analysis techniques. This course, covering in depth the principles and applications of correlation and contingency tables, is directly relevant to the daily work of a statistician. The course material discussing the logic, direction, and strength of correlation is helpful. The emphasis on recognizing patterns of association in contingency tables is also essential.
See salaries and explore the career path for Statistician
Research Analyst
A research analyst collects, analyzes, and interprets data to support research projects. This role benefits from understanding correlation and contingency, which are fundamental statistical concepts covered in this course. The course will help you to identify relationships between different variables and to analyze contingency tables to find significant patterns. This will serve any research analyst. This course provides a solid introduction to the statistical methods that is beneficial to a research analyst.
See salaries and explore the career path for Research Analyst
Market Research Analyst
A market research analyst studies consumer behavior to provide insights that guide business strategy. This role involves understanding relationships between various factors, such as demographics and consumer preferences. This course, focusing on measures of correlation and contingency, is very helpful to analyze the data and determine the strength and direction of these relationships. This course will help you learn to identify patterns with contingency tables, which is often at the heart of evaluating market segments. A market research analyst must use data to draw conclusions. This course will help build a foundation in key data analysis tools.
See salaries and explore the career path for Market Research Analyst
Data Scientist
Data scientists use statistical techniques to analyze complex data sets and extract actionable insights. A data scientist must be adept at identifying correlations between variables, and this course specifically teaches about these techniques. The course's focus on contingency tables will further help a data scientist to recognize patterns and relationships in their data. This course helps you learn how to determine when correlation and other statistical methods are appropriate, so it is helpful in a data scientist role.
See salaries and explore the career path for Data Scientist
Psychometrician
Psychometricians specialize in the design and analysis of psychological tests and assessments. They heavily rely on measures of correlation to establish the reliability and validity of these instruments, and this course covers these measures. The course helps you understand the logic behind identifying appropriate scenarios for using correlation. You will also learn to describe strength and direction. Contingency table analysis can be useful when examining relationships between categorical variables in psychological measurements. A psychometrician would find this course particularly helpful.
See salaries and explore the career path for Psychometrician
Epidemiologist
Epidemiologists investigate patterns and causes of health-related events, using statistical methods. Understanding correlation and contingency is crucial in this role to find risk factors and associations. This course, which covers these topics thoroughly, is beneficial to an epidemiologist. This course will help you to identify relationships and use contingency tables to analyze data. An important part of the work of an epidemiologist is understanding patterns of disease, and this course provides the relevant skills.
See salaries and explore the career path for Epidemiologist
Business Intelligence Analyst
Business intelligence analysts transform raw data into insights that drive business decisions. This position requires using statistical methods, and this course in measures of correlation and contingency is relevant to the position. The course emphasizes recognizing patterns of association within contingency tables, and this is essential for a business intelligence analyst. This course will help you in the role by improving your abilities to identify relationships in business data. This course is helpful both in its presentation of correlation and its presentation of contingency tables.
See salaries and explore the career path for Business Intelligence Analyst
Survey Researcher
Survey researchers design, administer, and analyze surveys. This role uses measures of correlation and contingency to understand relationships between responses and demographics. This course is relevant to this role, as it covers these statistical techniques in depth. This course will be helpful in particular in learning how to interpret relationships between variables and how to use contingency tables to identify patterns in survey data. A survey researcher could make practical use of the concepts in this course.
See salaries and explore the career path for Survey Researcher
Quantitative Analyst
Quantitative analysts apply mathematical and statistical models to financial data. This position benefits significantly from a solid understanding of correlation, which is a technique directly taught by this course. The ability to discern correlation relationships is key to many quantitative analysts. While financial modeling may involve more advanced topics, the core principles of correlation analysis and understanding contingency tables will help build a foundation for this role. The course material on the direction and strength of correlations is important.
See salaries and explore the career path for Quantitative Analyst
Biostatistician
Biostatisticians use statistical methods to solve problems in biology and health. The techniques of correlation and contingency, which are the focus of the course, are used in this position. A biostatistician uses these techniques to understand the relationship between variables. This course will also assist in the analysis of patterns within contingency tables. This course may be helpful for biostatisticians.
See salaries and explore the career path for Biostatistician
Risk Analyst
Risk analysts assess potential risks and recommend strategies to mitigate them. The role often uses statistical techniques to identify correlations and relationships between variables. A risk analyst will need to understand relationships, and this course helps to explain the meaning of correlation. The module on contingency table analysis can help you to identify and interpret patterns in risk scenarios. This course can be useful when approaching a risk analyst role.
See salaries and explore the career path for Risk Analyst
Financial Analyst
Financial analysts provide guidance to businesses and individuals making investment decisions. They can benefit from understanding relationships between market variables. While the course does not delve into finance in particular, an understanding of the core principles of correlation and its meaning, as covered in this course, may be useful for this kind of work. The course module on contingency table analysis may also be beneficial when examining categorical data. This course may be useful to those considering a financial analyst role.
See salaries and explore the career path for Financial Analyst
Social Science Researcher
A social science researcher investigates human behavior and social structures, often using statistical methods. The course provides helpful training in the use of correlation and contingency tables, which are important techniques in social science research. The analysis of contingency tables, as taught in this course, will help researchers recognize patterns and relationships. A social science researcher must understand how to apply correlation, and this course provides a good introduction to this. This course may be useful for social science research roles.
See salaries and explore the career path for Social Science Researcher
Policy Analyst
Policy analysts research and analyze policy issues to make recommendations in government or the non-profit sector. While a policy analyst performs diverse tasks, analyzing data from reports and studies is often central to their work. This course, teaching the applications of correlation and contingency tables, can be helpful in understanding data. This course may be useful for those who want to work as a policy analyst.
See salaries and explore the career path for Policy Analyst
Human Resources Analyst
A human resources analyst uses data to understand employee trends and improve HR practices. The course's material on correlation and contingency can be helpful in understanding relationships between different HR factors. The course can also help you understand how to identify patterns in contingency tables. This course may be useful to those wishing to become human resources analysts.
See salaries and explore the career path for Human Resources Analyst

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Measures of Correlation and Contingency.
Cover image
Essentials of Statistics for the Behavioral Sciences
Save
Provides a comprehensive introduction to statistical concepts relevant to behavioral sciences. It covers descriptive statistics, hypothesis testing, correlation, and regression. It commonly used textbook in undergraduate statistics courses. Reading this book will provide a solid foundation for understanding the measures of correlation and contingency covered in the course.
Essentials of Statistics for the Behavioral...
Paperback
$$$
Bundle: Essentials of Statistics for the Behavioral...
Product Bundle
$$$$
Bundle: Essentials of Statistics for the Behavioral...
Product Bundle
$$$$
Essentials of Statistics for the Behavioral...
Kindle Edition
$$$
Cover image
Discovering Statistics Using JASP
Save
Provides a practical guide to performing statistical analyses using SPSS. It covers correlation, regression, and contingency table analysis. It useful reference for students who want to learn how to apply statistical techniques to real-world data. This book is more valuable as additional reading than it is as a current reference.
Discovering Statistics Using JASP
Paperback
$$$$
Discovering Statistics Using JASP
Kindle Edition
$$$$

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Course image
Effort
5 weeks
Level
Introductory
Via
Coursera
Institution
American Psychological Association
Instructors
Mike Stadler, PhD
Peter Cardamone
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Offers APA student resources, which may be valuable for students pursuing coursework and career goals in psychology
Explores statistical relationships, which are fundamental for understanding research findings and data analysis in psychology
Covers contingency table analysis, which is essential for examining relationships between categorical variables in psychological research
Presented by the American Psychological Association, a leading organization in the field of psychology
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