Data Analysis for the Behavioral Sciences from edX

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.

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

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

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

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 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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

See salaries and explore the career path for Psychometrician

Data Analysis for the Behavioral Sciences

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