# Effect sizes and confidence intervals

Part 1 and Part 2 must be at least 150 – 200 words unless otherwise

Part 1: Effect Sizes and Confidence Intervals

For this discussion, begin by reviewing the techniques of effect sizes and confidence intervals in your textbook. Then, keeping these techniques in mind, read the following quotes:

· “Statistics are no substitute for judgment.”—Henry Clay

· “To not look at the data is foolish, but to look at the data as having all the answers is even more foolish. It is a collision of new-school statistics and statisticians against old-school managers, coaches, and instructors. Neither side is right, neither is wrong; there is so much to be gained from listening to both sides.”—Tim Kurkjian, I’m Fascinated by Sacrifice Flies: Inside the Game We All Love(2016)

· “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.”—Mark Twain

· “Good statistical inference never strays very far from the data.”—Brian S. Yandell (2007)

· “An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.”—John Tukey

Based on the above quotes, along with this week’s assigned readings and Instructor Guidance, discuss the importance of effect sizes and confidence intervals in research.

Part 2: Examples of Effect Sizes and Confidence Intervals in Research

Locate an example of a research study that uses effect sizes and confidence intervals in its analysis. Explain what these have allowed the researchers to accomplish and/or conclude in the study.

Required Resource

### Text

Lind, D. A., Marchal, W. G., & Wathen, S. A. (2017). Statistical techniques in business and economics. (17th ed.). Retrieved from http://connect.mheducation.com/class/

· Chapter 9: Estimation and Confidence Intervals

· Chapter 10: One-Sample Tests of Hypothesis

· Chapter 11: Two-Sample Tests of Hypothesis

· Chapter 12: Analysis of Variance

· Chapter 13: Correlation and Linear Regression

· Chapter 15: Nonparametric Methods: Nominal Level Hypothesis Tests

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