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Mike Stadler
Can you think of an area of your life that is influenced by statistics? Many times when we think about statistics in our daily lives, we think about numerical expressions of statistics, such as the number of daily COVID cases in our county, the percentage of students admitted each year to our university, or the number of people that voted in the last election. From each of these examples, we could go on to make inferences or look to answer questions based on this data, such as whether to open restaurants, how many new students are psychology majors, or if a specific issue drove voters to the polls in a specific state.
Read more
Can you think of an area of your life that is influenced by statistics? Many times when we think about statistics in our daily lives, we think about numerical expressions of statistics, such as the number of daily COVID cases in our county, the percentage of students admitted each year to our university, or the number of people that voted in the last election. From each of these examples, we could go on to make inferences or look to answer questions based on this data, such as whether to open restaurants, how many new students are psychology majors, or if a specific issue drove voters to the polls in a specific state.
Read more
Can you think of an area of your life that is influenced by statistics? Many times when we think about statistics in our daily lives, we think about numerical expressions of statistics, such as the number of daily COVID cases in our county, the percentage of students admitted each year to our university, or the number of people that voted in the last election. From each of these examples, we could go on to make inferences or look to answer questions based on this data, such as whether to open restaurants, how many new students are psychology majors, or if a specific issue drove voters to the polls in a specific state.
This course will begin by introducing the basic concepts of how to describe and visualize data, the fundamentals of using statistics to make inferences, and the logic of null hypothesis testing. Various types of hypothesis tests will be introduced, along with criteria for selecting which is appropriate for different study conditions. As an extension of null hypothesis significance tests, you will learn about how to interpret effect sizes and confidence intervals, along with statistical power, before being introduced to alternatives to null hypothesis significance testing. All this is fleshed out in Data Analysis for the Behavioral Sciences.
Register for this course and see more details by visiting:
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What's inside
Learning objectives
- Explain various ways to categorize variables.
- Explain various ways to describe data.
- Describe how graphs are used to visualize data.
- Explain the meaning of a correlation coefficient.
- Describe the logic of inferential statistics.
- Explain the logic of null hypothesis significance testing.
- Select the appropriate inferential test based on study criteria.
- Compare and contrast the use of statistical significance, effect size, and confidence intervals.
- Explain the importance of statistical power.
- Describe how alternative procedures address the major objections to null hypothesis significance testing.
- Explain various ways to categorize variables.
- Explain various ways to describe data.
- Describe how graphs are used to visualize data.
- Explain the meaning of a correlation coefficient.
- Describe the logic of inferential statistics.
- Explain the logic of null hypothesis significance testing.
- Select the appropriate inferential test based on study criteria.
- Compare and contrast the use of statistical significance, effect size, and confidence intervals.
- Explain the importance of statistical power.
- Describe how alternative procedures address the major objections to null hypothesis significance testing.
Syllabus
Data Analysis for the Behavioral Sciences
Learning Plan
Data Analysis Basics
Variables and Measures
Read more
Syllabus
Data Analysis for the Behavioral Sciences
Learning Plan
Data Analysis Basics
Variables and Measures
Read more
Describing Data
Section Summary
Null Hypothesis Significance Testing
Inferential Statistics
The Variety of Null Hypothesis Significance Tests
Beyond Null Hypothesis Significance Testing
Preview
The “New Statistics”
Statistical Power
Alternatives to Null Hypothesis Significance Testing
Course Summary
Explain various ways to categorize variables
Explain various ways to describe data
Explain the meaning of a correlation coefficient
Describe the logic of inferential statistics
Explain the logic of null hypothesis significance testing
Select the appropriate inferential test based on study criteria
Compare and contrast the use of statistical significance, effect size, and confidence intervals
Explain the importance of statistical power
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops skills in identifying and describing variables, a skill set foundational to data interpretation
Taught by instructors Mike Stadler with subject matter expertise in data analysis
Examines the statistical tools and processes used to make inferences in data analysis
Introduces various hypothesis tests, a cornerstone of the data analysis process
Covers statistical significance, effect size, and confidence intervals, key concepts for understanding statistical results
Develops an understanding of the importance of statistical power, a crucial aspect of data analysis design
Save this course
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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 Data Analysis for the Behavioral Sciences with these
activities:
Organize and review course notes, assignments, and materials
Show steps
Stay organized and periodically review course materials to enhance retention and recall.
Show steps
-
Set up a system for organizing notes and materials
-
Review and summarize key concepts from lectures and readings
-
Complete practice questions or exercises to reinforce your understanding
Review data visualization and statistical analysis techniques
Show steps
Brush up on the basics of data visualization and statistical analysis to strengthen your foundation for this course.
Browse courses on
Data Visualization
Show steps
-
Review concepts of descriptive statistics, such as mean, median, and standard deviation
-
Revisit different types of data visualizations, such as bar charts, scatterplots, and histograms
-
Try using a statistical software package, such as R or Python
Review Basic Statistical Concepts
Show steps
Refresh your knowledge of basic statistical concepts to prepare for the more advanced topics covered in this course.
Browse courses on
Descriptive Statistics
Show steps
-
Review notes from a previous statistics course or textbook.
-
Take an online practice quiz or exam to assess your understanding.
-
Consult with a tutor or instructor if needed.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Understanding Psychological Research
Show steps
Understand the principles of psychological research, including design, methods, and analysis.
Show steps
-
Read the first few chapters of the book to gain an overview of psychological research.
-
Attend the first few lectures of the course to gain a deeper understanding of the material.
-
Discuss the material with classmates and the instructor to clarify and reinforce your understanding.
Explore Data Analysis Software
Show steps
Become familiar with the features and functionality of data analysis software to enhance your ability to analyze and interpret data.
Browse courses on
Data Analysis
Show steps
-
Choose a data analysis software package, such as R or Python.
-
Find online tutorials or documentation for the software.
-
Follow the tutorials to learn the basics of the software, such as data import, data manipulation, and statistical analysis.
-
Practice using the software on your own by analyzing a small dataset.
Join or form a study group to discuss course topics and share insights
Show steps
Collaborate with peers to discuss difficult concepts, share resources, and reinforce your understanding through group discussions.
Show steps
-
Find or form a study group with classmates
-
Meet regularly to discuss course material and assignments
-
Work together to solve problems and clarify concepts
Explore resources on statistical significance, effect size, and confidence intervals
Show steps
Find online tutorials and resources to enhance your understanding of statistical significance and related concepts.
Browse courses on
Statistical Significance
Show steps
-
Use search engines or academic databases to find reputable resources
-
Watch videos or read articles on the topic
-
Complete practice exercises or quizzes to test your comprehension
Practice Calculating and Interpreting Correlation Coefficients
Show steps
Improve your ability to calculate and interpret correlation coefficients, which are used to measure the strength and direction of the relationship between two variables.
Browse courses on
Correlation and Regression
Show steps
-
Find a set of online practice problems or exercises on calculating and interpreting correlation coefficients.
-
Solve the problems and check your answers against the provided solutions.
-
Review the concepts and formulas for calculating and interpreting correlation coefficients as needed.
Participate in a Study Group
Show steps
Enhance your understanding of the course material by discussing and working together with a group of peers.
Browse courses on
Collaboration
Show steps
-
Find a group of classmates who are willing to meet regularly to study and discuss the course material.
-
Set up a regular meeting time and location.
-
Discuss the assigned readings, lecture notes, and practice problems.
-
Collaborate on assignments and projects.
Solve practice problems on hypothesis testing and data analysis
Show steps
Regular practice through problem-solving will strengthen your analytical skills and reinforce course concepts.
Browse courses on
Hypothesis Testing
Show steps
-
Find online practice problems or textbooks with exercises
-
Solve problems independently
-
Check your answers and identify areas for improvement
Create a Hypothesis and Design a Study
Show steps
Develop your skills in creating hypotheses and designing research studies by completing this project.
Browse courses on
Research Methods in Psychology
Show steps
-
Identify a research question that you are interested in.
-
Formulate a hypothesis that predicts the relationship between two or more variables.
-
Design a study to test your hypothesis, including the selection of participants, the type of data to be collected, and the methods of data analysis.
-
Write a brief proposal outlining your hypothesis, study design, and expected outcomes.
Create a Visual Representation of a Statistical Analysis
Show steps
Develop your skills in communicating statistical findings by creating a visual representation of a data analysis.
Browse courses on
Data Visualization
Show steps
-
Select a statistical analysis that you have conducted or one that is provided in the course materials.
-
Choose an appropriate visual representation for the analysis, such as a graph, chart, or infographic.
-
Design and create the visual representation, ensuring that it is clear, accurate, and visually appealing.
-
Write a brief explanation of the visual representation and its implications.
Develop a data visualization dashboard for a real-world dataset
Show steps
Apply your skills to create a practical and interactive data visualization that showcases your understanding of the course material.
Browse courses on
Data Visualization
Show steps
-
Choose a relevant dataset and identify the key variables
-
Design and create visualizations that effectively communicate the insights
-
Develop an interactive dashboard using a tool like Tableau or Power BI
-
Present your dashboard, explaining the data and the insights you gained
Participate in a Data Analysis Competition
Show steps
Challenge yourself and apply your data analysis skills by participating in a competition.
Browse courses on
Data Analysis
Show steps
-
Find a data analysis competition that aligns with your interests.
-
Download the competition data and familiarize yourself with the problem statement.
-
Develop a data analysis approach and implement it using the software of your choice.
-
Submit your results to the competition and analyze your performance.
Organize and review course notes, assignments, and materials
Show steps
Stay organized and periodically review course materials to enhance retention and recall.
Show steps
Show steps
Show steps
- Set up a system for organizing notes and materials
- Review and summarize key concepts from lectures and readings
- Complete practice questions or exercises to reinforce your understanding
Review data visualization and statistical analysis techniques
Show steps
Brush up on the basics of data visualization and statistical analysis to strengthen your foundation for this course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Review concepts of descriptive statistics, such as mean, median, and standard deviation
- Revisit different types of data visualizations, such as bar charts, scatterplots, and histograms
- Try using a statistical software package, such as R or Python
Review Basic Statistical Concepts
Show steps
Refresh your knowledge of basic statistical concepts to prepare for the more advanced topics covered in this course.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Review notes from a previous statistics course or textbook.
- Take an online practice quiz or exam to assess your understanding.
- Consult with a tutor or instructor if needed.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Understanding Psychological Research
Show steps
Understand the principles of psychological research, including design, methods, and analysis.
Show steps
Show steps
Show steps
- Read the first few chapters of the book to gain an overview of psychological research.
- Attend the first few lectures of the course to gain a deeper understanding of the material.
- Discuss the material with classmates and the instructor to clarify and reinforce your understanding.
Explore Data Analysis Software
Show steps
Become familiar with the features and functionality of data analysis software to enhance your ability to analyze and interpret data.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Choose a data analysis software package, such as R or Python.
- Find online tutorials or documentation for the software.
- Follow the tutorials to learn the basics of the software, such as data import, data manipulation, and statistical analysis.
- Practice using the software on your own by analyzing a small dataset.
Join or form a study group to discuss course topics and share insights
Show steps
Collaborate with peers to discuss difficult concepts, share resources, and reinforce your understanding through group discussions.
Show steps
Show steps
Show steps
- Find or form a study group with classmates
- Meet regularly to discuss course material and assignments
- Work together to solve problems and clarify concepts
Explore resources on statistical significance, effect size, and confidence intervals
Show steps
Find online tutorials and resources to enhance your understanding of statistical significance and related concepts.
Browse courses on
Statistical Significance
Show steps
Show steps
Show steps
- Use search engines or academic databases to find reputable resources
- Watch videos or read articles on the topic
- Complete practice exercises or quizzes to test your comprehension
Practice Calculating and Interpreting Correlation Coefficients
Show steps
Improve your ability to calculate and interpret correlation coefficients, which are used to measure the strength and direction of the relationship between two variables.
Browse courses on
Correlation and Regression
Show steps
Show steps
Show steps
- Find a set of online practice problems or exercises on calculating and interpreting correlation coefficients.
- Solve the problems and check your answers against the provided solutions.
- Review the concepts and formulas for calculating and interpreting correlation coefficients as needed.
Participate in a Study Group
Show steps
Enhance your understanding of the course material by discussing and working together with a group of peers.
Browse courses on
Collaboration
Show steps
Show steps
Show steps
- Find a group of classmates who are willing to meet regularly to study and discuss the course material.
- Set up a regular meeting time and location.
- Discuss the assigned readings, lecture notes, and practice problems.
- Collaborate on assignments and projects.
Solve practice problems on hypothesis testing and data analysis
Show steps
Regular practice through problem-solving will strengthen your analytical skills and reinforce course concepts.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Find online practice problems or textbooks with exercises
- Solve problems independently
- Check your answers and identify areas for improvement
Create a Hypothesis and Design a Study
Show steps
Develop your skills in creating hypotheses and designing research studies by completing this project.
Browse courses on
Research Methods in Psychology
Show steps
Show steps
Show steps
- Identify a research question that you are interested in.
- Formulate a hypothesis that predicts the relationship between two or more variables.
- Design a study to test your hypothesis, including the selection of participants, the type of data to be collected, and the methods of data analysis.
- Write a brief proposal outlining your hypothesis, study design, and expected outcomes.
Create a Visual Representation of a Statistical Analysis
Show steps
Develop your skills in communicating statistical findings by creating a visual representation of a data analysis.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Select a statistical analysis that you have conducted or one that is provided in the course materials.
- Choose an appropriate visual representation for the analysis, such as a graph, chart, or infographic.
- Design and create the visual representation, ensuring that it is clear, accurate, and visually appealing.
- Write a brief explanation of the visual representation and its implications.
Develop a data visualization dashboard for a real-world dataset
Show steps
Apply your skills to create a practical and interactive data visualization that showcases your understanding of the course material.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a relevant dataset and identify the key variables
- Design and create visualizations that effectively communicate the insights
- Develop an interactive dashboard using a tool like Tableau or Power BI
- Present your dashboard, explaining the data and the insights you gained
Participate in a Data Analysis Competition
Show steps
Challenge yourself and apply your data analysis skills by participating in a competition.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find a data analysis competition that aligns with your interests.
- Download the competition data and familiarize yourself with the problem statement.
- Develop a data analysis approach and implement it using the software of your choice.
- Submit your results to the competition and analyze your performance.
Career center
Learners who complete Data Analysis for the Behavioral Sciences will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They use statistical analysis, machine learning, and other techniques to extract insights from data. This course can help you develop the skills you need to become a successful Data Scientist by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Data Analyst
Data Analyst
Data Analysts use data to make informed decisions that benefit businesses. They use statistical analysis and data mining to identify trends and patterns in data. This course can help you develop the skills you need to become a successful Data Analyst by teaching you how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests. You will also learn about effect sizes, confidence intervals, and statistical power.
Statistician
Statistician
Statisticians use statistical methods to collect, analyze, interpret, and present data. They work in a variety of fields, including finance, healthcare, and marketing. This course can help you develop the skills you need to become a successful Statistician by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They work for investment banks, hedge funds, and other financial institutions. This course can help you develop the skills you need to become a successful Quantitative Analyst by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Business Analyst
Business Analyst
Business Analysts use data to help businesses improve their operations. They use statistical analysis and other techniques to identify inefficiencies and opportunities for improvement. This course can help you develop the skills you need to become a successful Business Analyst by teaching you how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They work in a variety of fields, including manufacturing, logistics, and healthcare. This course can help you develop the skills you need to become a successful Operations Research Analyst by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make investment recommendations. They work for investment banks, hedge funds, and other financial institutions. This course can help you develop the skills you need to become a successful Financial Analyst by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Data Architect
Data Architect
Data Architects design and manage data systems. They work with data scientists, engineers, and other IT professionals to ensure that data is available and usable for analysis. This course can help you develop the skills you need to become a successful Data Architect by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk. They work for insurance companies, pension funds, and other financial institutions. This course can help you develop the skills you need to become a successful Actuary by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes of disease and injury. They use statistical methods to analyze data and identify risk factors. This course can help you develop the skills you need to become a successful Epidemiologist by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to analyze biological data. They work in a variety of fields, including medicine, public health, and genetics. This course can help you develop the skills you need to become a successful Biostatistician by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Market Researcher
Market Researcher
Market Researchers gather and analyze data about consumers and markets. They use this data to help businesses understand their customers and make better decisions. This course can help you develop the skills you need to become a successful Market Researcher by teaching you how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Econometrician
Econometrician
Econometricians use statistical methods to analyze economic data. They work in a variety of fields, including finance, economics, and public policy. This course can help you develop the skills you need to become a successful Econometrician by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Survey Researcher
Survey Researcher
Survey Researchers design and conduct surveys to collect data about populations. They use statistical methods to analyze data and make inferences. This course can help you develop the skills you need to become a successful Survey Researcher by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
Psychometrician
Psychometrician
Psychometricians develop and use statistical methods to measure psychological traits and abilities. They work in a variety of fields, including education, psychology, and human resources. This course can help you develop the skills you need to become a successful Psychometrician by teaching you the fundamentals of statistics, including how to describe and visualize data, use inferential statistics to make inferences, and conduct hypothesis tests.
For more career information including salaries, visit:
OpenCourser.com/course/pghujn/data
Reading list
We've selected nine 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
Data Analysis for the Behavioral Sciences.
Is designed to accompany an introductory statistics course for students in the behavioral sciences. It provides a clear and concise explanation of statistical concepts, with a focus on practical applications.
Provides a comprehensive overview of statistical concepts and techniques, with a focus on using IBM SPSS Statistics software. It would be a valuable supplement to the course, providing additional examples and exercises.
Provides a comprehensive introduction to statistical learning methods, with a focus on modern techniques such as machine learning and data mining. It would be a valuable reference for students in the course who are interested in learning more about these topics.
Provides a comprehensive overview of statistical methods used in the social and health sciences, with a focus on practical applications. It would be a valuable reference for students in the course who are interested in learning more about the specific statistical techniques used in these fields.
Provides a comprehensive overview of statistical methods used in psychology, with a focus on practical applications. It would be a valuable reference for students in the course who are interested in learning more about the specific statistical techniques used in psychology.
Provides a comprehensive overview of statistical power analysis, which is the process of determining the minimum sample size needed to achieve a desired level of statistical significance. It would be a valuable reference for students in the course who are interested in learning more about this topic.
Provides a non-technical introduction to statistics, with a focus on developing conceptual understanding. It would be a valuable supplement to the course, providing a different perspective on statistical concepts.
Provides a non-technical introduction to statistical thinking, with a focus on developing critical thinking skills. It would be a valuable supplement to the course, providing a different perspective on statistical concepts.
Provides a critical examination of null hypothesis significance testing, and argues that it flawed method of statistical inference. It would be a valuable supplement to the course, providing a different perspective on statistical methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/pghujn/data
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Effort
2 to 5 hours per week for 8 weeks
Level
Introductory
Via
edX
Institution
American Psychological Association
Instructor
Mike Stadler
Session
April 16, 2024
- April 15, 2025
Language
English
Transcript
English
Good to know
Develops skills in identifying and describing variables, a skill set foundational to data interpretation
Taught by instructors Mike Stadler with subject matter expertise in data analysis
Examines the statistical tools and processes used to make inferences in data analysis
Introduces various hypothesis tests, a cornerstone of the data analysis process
Covers statistical significance, effect size, and confidence intervals, key concepts for understanding statistical results
Develops an understanding of the importance of statistical power, a crucial aspect of data analysis design
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