It's important to understand that hypothesis testing is just how statisticians (by "statisticians" I mean people who are working with data, e.g. analysts, auditors, economists, whoever) answer quanitative questions. We intuitively know that not much is truly certain, and that it's really hard (if not impossible) to collect data on everything we are curious about. So we use samples and try to extrapolate to a larger population. For this discussion, I would like each of you to come up with your own interesting hypothesis test. So, you will do the following: 1) Explain the context or story for which you have a problem stats might be able to help with. 2) Come up with the null and alternative hypotheses. This can be in words, or numbers, or a combination of both (I'll give an example below). 3) Explain where/how you might collect data to reach a conclusion for the test.
It's important to understand that hypothesis testing is just how statisticians (by "statisticians" I mean people who are working with data, e.g. analysts, auditors, economists, whoever) answer quanitative questions. We intuitively know that not much is truly certain, and that it's really hard (if not impossible) to collect data on everything we are curious about. So we use samples and try to extrapolate to a larger population. For this discussion, I would like each of you to come up with your own interesting hypothesis test. So, you will do the following: 1) Explain the context or story for which you have a problem stats might be able to help with. 2) Come up with the null and alternative hypotheses. This can be in words, or numbers, or a combination of both (I'll give an example below). 3) Explain where/how you might collect data to reach a conclusion for the test.
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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It's important to understand that hypothesis testing is just how statisticians (by "statisticians" I mean people who are working with data, e.g. analysts, auditors, economists, whoever) answer quanitative questions. We intuitively know that not much is truly certain, and that it's really hard (if not impossible) to collect data on everything we are curious about. So we use samples and try to extrapolate to a larger population. For this discussion, I would like each of you to come up with your own interesting hypothesis test. So, you will do the following:
1) Explain the context or story for which you have a problem stats might be able to help with.
2) Come up with the null and alternative hypotheses. This can be in words, or numbers, or a combination of both (I'll give an example below).
3) Explain where/how you might collect data to reach a conclusion for the test.
4) (RESPONSE) When you respond to someone else's post, I want you to critique their test and data. If you can, suggest a way it might be improved (better data collection, asking a better question, etc.).
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