University of Colorado Boulder - Data Driven Decision Making
- Offered byCoursera
Data Driven Decision Making at Coursera Overview
Duration | 12 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Driven Decision Making at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 3 in the The Data Driven Manager Specialization
- Intermediate Level Algebra recommended.
- Approx. 12 hours to complete
- English Subtitles: English
Data Driven Decision Making at Coursera Course details
- Once we have generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and business professionals need to know which test or tests to use. Through this class, you will be able to perform one sample tests for comparison to historical data. You will also be able to determine statistically significant relationships between two variables. You will be able to perform two sample tests for both independent and dependent data. Finally, you will analyze data with more than two groups using the Analysis of Variance.
- This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.
Data Driven Decision Making at Coursera Curriculum
One Sample Tests
Welcome to Data Driven Decision Making
Introduction to One Sample Tests
One Sample Tests and Hypothesis Testing Part 1
One Sample Tests and Hypothesis Testing Part 2
The One Sample Normal (Z) Test for the Mean Part 1
The One Sample Normal (Z) Test for the Mean Part 2
The One Sample t Test for the Mean Part 1
The One Sample t Test for the Mean Part 2
The Chi Square Test for Variance Part 1
The Chi Square Test for Variance Part 2
The One Sample Exact Binomial Test Part 1
The One Sample Exact Binomial Test Part 2
The Wilcoxon Signed Ranks Test for Location Part 1
The Wilcoxon Signed Ranks Test for Location Part 2
The One Sample Poisson Test Part 1
The One Sample Poisson Test Part 2
Welcome and Where to Find Help
One Sample Tests
Correlation and Association
Introduction to Correlation and Association
Correlation and Association
Correlation and Scatterplots
The One Sample t Test for Correlation
Fisher’s Z Test for Correlation
Spearman’s Rank-Order Correlation
Point Biserial Correlation
Cross Tabulation and Categorical Data Formats
Calculating the Chi Square Statistic
Measures of Association
Correlation and Association
Two Sample Tests for Independent Data
Introduction to Two Sample Tests for Independent Data
Independent vs Dependent Samples
Two Sample Equal Variance t Test for Means
Two Sample Equal Variance t Test for Means Practice Problem
Two Sample Unequal Variance t Test for Means
Two Sample Unequal Variance t Test for Means Practice Problem
Two Independent Sample F Test for Variances
Two Independent Sample F Test for Variances Practice Problem
The Levene Test for Dispersion and the ADM(n-1) Procedure
Fisher’s Exact Test
Fisher’s Exact Test Example
Two Independent Sample Poisson Rate Test
Two Independent Sample Poisson Rate Test Example
Wilcoxon Mann Whitney Test
Wilcoxon Mann Whitney Test Example
Two Sample Tests for Independent Data
Two Sample Tests for Dependent Data
Introduction to Two Sample Tests for Dependent Data
Introduction to Two Sample Dependent Tests
The Repeated Measures t Test
Creating a Scatterplot with an ISO Line
The Repeated Measures t Test Example
The Matched Pairs t Test
The Matched Pairs t Test Example
The Two Sample Dependent t Test for Variances
The Two Sample Dependent t Test for Variances Example
McNemar’s Test for Change
McNemar’s Test for Change Example
The Wilcoxon Signed Ranks Test
Wilcoxon Signed Ranks Test Example
Pre Post Test Introduction
Problem 1 Pre Test Groups
Problem 2 Pre Post Test Group 1
Problem 3 Pre Post Test Group 2
Problem 4 Post Test Groups
Two Sample Tests for Dependent Data
The One Way Analysis of Variance
Introduction to One Way ANOVA
The One Way Analysis of Variance
ANOVA Principles
One Way ANOVA for Means
The ANOVA Source Table
ANOVA Assumptions and Welch's ANOVA
Data Visualization for ANOVA
Statistical Importance
One Way ANOVA for Dispersion
Post Hoc Analysis
Roadmap for the One Way ANOVA Part 1
Roadmap for the One Way ANOVA Part 2
Roadmap for the One Way ANOVA Part 3
One Way ANOVA
Data Driven Decision Making at Coursera Admission Process
Important Dates
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