Statistics in Psychological Research
- Offered byCoursera
Statistics in Psychological Research at Coursera Overview
Duration | 11 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Statistics in Psychological Research at Coursera Highlights
- Earn a certificate from American Psychological Association
- Add to your LinkedIn profile
- 27 assignments
Statistics in Psychological Research at Coursera Course details
- What you'll learn
- Explain ways to categorize variables and describe data.
- Describe how graphs are used to visualize data.
- Describe the logic of inferential statistics and null hypothesis significance testing.
- Select the appropriate inferential test based on 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.
- This is primarily aimed at first- and second-year undergraduates interested in psychology, statistics, data analysis, and research methods along with high school students and professionals with similar interests
Statistics in Psychological Research at Coursera Curriculum
Learn With PsycLearn Essentials
Get Started With PsycLearn Essentials!
Metacognitive Checkpoints: Pause and Reflect on Your Learning
Welcome to PsycLearn Essentials
Requirements to Earn a Coursera Specialization Certificate
What’s in Your Course
Coursera Honor Code and Discussion Forum Policy
Study Tips for Success in PsycLearn Essentials
Additional Information
Introduction to Statistics for Psychological Research
Welcome
Data Analysis for the Behavioral Sciences
Data Analysis Basics
The Heart of Statistics
Making Distinctions
Levels of Measurement
Roles Variables Play
Summarizing Data
Describing Data With Univariate Frequency Distributions
Measures of Central Tendency
Variability
Describing Data With Bivariate Graphs
Correlation and Causation
Practice With Variables
Review: Types of Variables
The Importance of Level of Measurement
Review: Levels of Measurement
Frequency Polygons
Describing Data With Univariate Descriptive Statistics
Review of Describing Univariate Data
Describing Data With Bivariate Descriptive Statistics: Correlation
Review of Describing Bivariate Data
Key Takeaways: Data Analysis Basics
DOWNLOAD: Characteristics of Variables
DOWNLOAD: Correlations
Practice Identifying Types of Variables
Check Your Understanding: Types of Variables
Practice With Levels of Measurement
Check Your Understanding: Levels of Measurement
Check Your Understanding: Roles Variables Play
Check Your Understanding: Describing Univariate Data
Check Your Understanding: Describing Bivariate Data
Mastering the Content: Data Analysis Basics
Null Hypothesis Significance Testing
Probability
Normal Distributions
Parametric Tests
John Arbuthnot’s Null Hypothesis
The Logic of Null Hypothesis Significance Testing
An Illustration of NHST in Action
The Results of the Null Hypothesis Significance Testing Process
Selecting a Statistical Test
Nonparametric Alternatives
Foundations of Inferential Statistics
Probability Distributions in Inferential Statistics
Review of Foundations of Inferential Statistics
The Basics of Null Hypothesis Significance Testing
Further Illustration of NHST
Type I and Type II Errors
Review of Null Hypothesis Significance Testing
Selecting the Appropriate Hypothesis Test
Tests for Differences Among Group Means
Investigating Relationships Between Variables
Nonparametric Tests
Tests of Relationships in Frequency of Occurrence
Review of the Variety of Null Hypothesis Significance Tests
Key Takeaways: Null Hypothesis Significance Testing
DOWNLOAD: Normal Distributions
DOWNLOAD: Type I and Type II Errors
Check Your Understanding: Inferential Statistics
Check Your Understanding: Null Hypothesis Significance Testing
Check Your Understanding: The Variety of Null Hypothesis Significance Tests
Mastering the Content: Null Hypothesis Significance Testing
Beyond Null Hypothesis Significance Testing
What Are p Values?
Effect Size
Confidence Intervals
More Complete Reporting of Results
Statistical Power
Determining Statistical Power
Bayesian Inference
Estimation Methods
Meta-Analysis
Modeling
Further Consideration of Confidence Intervals
Review of the New Statistics
Graphing Power
Determining Power
Determining Power, Continued
Review of Statistical Power
Objections to Null Hypothesis Significance Testing Methods
Alternatives to Null Hypothesis Significance Testing Methods
Bayesian Hypothesis Testing
Review of Alternatives to Null Hypothesis Significance Testing
Key Takeaways: Beyond Null Hypothesis Significance Testing
DOWNLOAD: Confidence Intervals
DOWNLOAD: Power
Check Your Understanding: The New Statistics
Check Your Understanding: Statistical Power
Check Your Understanding: Alternatives to Null Hypothesis Significance Testing
Mastering the Content: Beyond Null Hypothesis Significance Testing
Conclusion
Course Assessment
Closing Remarks
Course Quiz: Statistics for Psychological Research
Resources from the American Psychological Association
Statistics in Psychological Research at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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