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a. why variability is important to measure, and what higher variability does to your chances of significance and your overall confidence in your result b. relationship between power and sample size c. how things like variability, sample size, and effect size effect the size of obtained t-scores and F ratios d. the difference between positive and negative correlation, the difference between correlation and causation e. the difference between type I and type II errors and how we either measure the risk of or control for these errors (HINT: your alpha is important for one of these, power for the other) f. what sampling error is and what it has to do with hypothesis testing g. general terminology like "null hypothesis," "alternative hypothesis," "independent variable," etc.

a. why variability is important to measure, and what higher variability does to your chances of significance and your overall confidence in your result b. relationship between power and sample size c. how things like variability, sample size, and effect size effect the size of obtained t-scores and F ratios d. the difference between positive and negative correlation, the difference between correlation and causation e. the difference between type I and type II errors and how we either measure the risk of or control for these errors (HINT: your alpha is important for one of these, power for the other) f. what sampling error is and what it has to do with hypothesis testing g. general terminology like "null hypothesis," "alternative hypothesis," "independent variable," etc.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Could you please explain these questions and definitions? 

a. why variability is important to measure, and what higher variability does to your chances of significance and your overall confidence in your result b. relationship between power and sample size c. how things like variability, sample size, and effect size effect the size of obtained t-scores and F ratios d. the difference between positive and negative correlation, the difference between correlation and causation e. the difference between type I and type II errors and how we either measure the risk of or control for these errors (HINT: your alpha is important for one of these, power for the other) f. what sampling error is and what it has to do with hypothesis testing g. general terminology like "null hypothesis," "alternative hypothesis," "independent variable," etc.
Transcribed Image Text:a. why variability is important to measure, and what higher variability does to your chances of significance and your overall confidence in your result b. relationship between power and sample size c. how things like variability, sample size, and effect size effect the size of obtained t-scores and F ratios d. the difference between positive and negative correlation, the difference between correlation and causation e. the difference between type I and type II errors and how we either measure the risk of or control for these errors (HINT: your alpha is important for one of these, power for the other) f. what sampling error is and what it has to do with hypothesis testing g. general terminology like "null hypothesis," "alternative hypothesis," "independent variable," etc.
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