Data Acquisition, Risk, and Estimation

Data Acquisition, Risk, and Estimation

This course is part of The Data Driven Manager Specialization

Instructor: Wendy Martin

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5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Create a plan to answer business and engineering questions.
Calculate effect size, power and sample size to reduce risk in decision making.
Distinguish between best- and worst-case scenarios given point and interval estimates.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

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Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the The Data Driven Manager Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

Engineering and Business professionals often have access to many sources of data. The best way to way to ensure your data is both valid and reliable is to plan for it ahead of time. Through this class, you will be able to plan for accurate and precise data generation, then use that data for the purpose of estimation and risk reduction related to capital investments.

This specialization 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.

Upon completion of this module, students will be able to classify types of sampling used for data acquisition, describe sampling error, and construct random number sequences for sampling.

What's included

12 videos2 readings1 assignment2 discussion prompts

12 videos Total 51 minutes

Welcome to Acquisition, Risk and Estimation 2 minutes
Introduction to Fundamentals of Sampling 1 minute
Sample Versus Population 4 minutes
Types of Sampling - Part 1 7 minutes
Types of Sampling - Part 2 4 minutes
Sampling Error 5 minutes
Random Sampling Distributions - Part 1 5 minutes
Random Sampling Distributions - Part 2 2 minutes
RSD of the Mean 7 minutes
The Central Limit Theorem 4 minutes
Solving Problems with the RSD of the Mean Part 1 4 minutes
Solving Problems with the RSD of the Mean Part 2 5 minutes

2 readings Total 11 minutes

Course Updates and Accessibility Support 1 minute
Non-Credit Students: Welcome and Where to Find Help 10 minutes

1 assignment Total 30 minutes

Fundamentals of Sampling 30 minutes

2 discussion prompts Total 20 minutes

Introduce Yourself! 10 minutes
Fundamentals of Sampling 10 minutes

Upon completion of this module, students will be able to calculate point and interval estimates using RStudio and ROIStat.

What's included

9 videos1 assignment1 discussion prompt

9 videos Total 38 minutes

Introduction to Estimation 1 minute
Estimators and Point Estimates 7 minutes
Interval Estimates 6 minutes
Confidence Interval for the Mean, Sigma Known 4 minutes
Confidence Interval for the Mean, Sigma Unknown 4 minutes
Confidence Interval for Variance / Standard Deviation 2 minutes
Confidence Interval for Proportion / Rate (Count) 4 minutes
Practice Activity 1 6 minutes
Practice Activities 2 and 3 4 minutes

1 assignment Total 30 minutes

Estimation 30 minutes

1 discussion prompt Total 10 minutes

Estimation 10 minutes

Upon completion of this module, students will be able to use point and interval estimates to determine best- and worst-case scenarios.

What's included

9 videos2 assignments1 discussion prompt

9 videos Total 38 minutes

Introduction to Best Case / Worst Case Analysis 1 minute
Best / Worst Case Analysis Introduction and Step 1 4 minutes
Best / Worst Case Analysis Steps 2 and 3 5 minutes
Best / Worst Case Analysis Steps 4 and 5 4 minutes
Creating the table using RStudio 6 minutes
Visualization and Joint Probability 3 minutes
Best / Worst Case Example 1 7 minutes
Best / Worst Case Example 2 Part 1 5 minutes
Best / Worst Case Example 2 Part 2 3 minutes

2 assignments Total 75 minutes

Best Case / Worst Case Analysis 45 minutes
Best / Worst Case Practice Quiz 30 minutes

1 discussion prompt Total 10 minutes

Best Case / Worst Case Analysis 10 minutes

Upon completion of this module, students will be able to plan for data acquisition to minimize risk in decision making, including sample size, effect size and power calculations.

What's included

12 videos1 assignment1 discussion prompt

12 videos Total 58 minutes

Introduction to Foundations of Hypothesis Testing 1 minute
Introduction to Hypothesis Testing 6 minutes
Testing Hypotheses 5 minutes
Significance Level, Risk, One-Two-Tailed Tests 7 minutes
Error and Power in Hypothesis Testing 5 minutes
Understanding Beta and Power 9 minutes
Calculating Beta and Power for Means 4 minutes
Calculating Beta and Power for Variance 2 minutes
Calculating Beta and Power for Proportions and Rates 4 minutes
Sample Size Calculations for Means 7 minutes
Sample Size Calculations for Variances 5 minutes
Sample Size Calculations for Proportions 4 minutes

1 assignment Total 30 minutes

Foundations of Hypothesis Testing 30 minutes

1 discussion prompt Total 10 minutes

Foundations of Hypothesis Testing 10 minutes

Upon completion of this module, students will be able to use return on investment calculations to determine effect size, sample size and power using RStudio and ROIStat.

What's included

11 videos2 assignments1 discussion prompt

11 videos Total 55 minutes

Introduction to Essentials for Effect Size Calculations 1 minute
Essentials for Effect Size Calculations 5 minutes
Risk Analysis - Implications of Decisions 7 minutes
Effect Size Calculation OSCD Example Part 1 5 minutes
Effect Size Calculation OSCD Example Part 2 5 minutes
Effect Size Calculation OSCD Example Part 3 6 minutes
Effect Size Calculation for the Mean Part 1 6 minutes
Effect Size Calculation for the Mean Part 2 5 minutes
Effect Size Calculation for the Mean Part 3 5 minutes
Effect Size Calculation for the Standard Deviation 5 minutes
Effect Size Calculation for the Proportion 5 minutes

2 assignments Total 60 minutes

Essentials for Effect Size Calculations 30 minutes
Effect Size Practice Quiz 30 minutes

1 discussion prompt Total 10 minutes

Essentials for Effect Size Calculations 10 minutes

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Build toward a degree

This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹