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.

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What You Will 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.

Syllabus

WEEK 1

Fundamentals of Sampling

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.

WEEK 2

Estimation

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

WEEK 3

Best Case / Worst Case Analysis

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

WEEK 4

Foundations of Hypothesis Testing

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.

WEEK 5

Essentials for Effect Size Calculations

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.

Data Acquisition

Data Analysis

Statistical Inference

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