Topics: Normal distribution, Central limit theorem, Type I and type II errors Pages: 3 (766 words) Published: December 5, 2012
ou have two friends - one lives in Hilo and the other in Kona. Both friends are encouraging you to move to their side of the island. Both assert that individuals on their side are emotionally healthier, physically healthier and live longer. You want to make the right decision and you decide to design a study to test the issue. Create a hypothesis for your study.


Residents of Hilo live longer, and are emotionally and physically healthier than residents from Kona because of the air quality.

What kind of general steps would you take to test your hypothesis - data collection, sampling, etc.?

Salkind describes that there are four initial steps to the data collection process. First, constructing a data form that is used to organize data. Second, designating a code to identify the data. Third, collecting the data. Fourth, entering the date into the data form.

Salkind also describes the process called the Ten Commandments of Data Collection (Salkind 2011), which helps to avoid errors in the data collection process. First, getting permission to collect your data. Second, start to think of what kind of data is needed. Third, thinkn about where the data will come from. Fourth, create an easy to use data form. Fifth, make a copy of the data file and save it elsewhere after transferring scores on to the data form. Sixth, do not allow anyone but yourself, unless extensively trained, to enter the data. Seventh, be sure to make a detailed schedule of when the data will be collected. Eight, research sources for data participants. Nine, follow up with participants who missed testing appointments. Ten, always keep every piece of data ever collected.

How does the Central Limit Theorem relate to your results?

The central limit theorem says that the sample should be larger than 30, but if it should be less than 30, you must use non parametric or distribution free means statistics that are not tied into the normal distribution, meaning it is...

References: Salkind, N.J. (2011). Exploring Research. (8thed.) New Jersey : Pearson. ISBN 10 : 9780205093816
Basically this theory is a part of all statistics that rely on normality as a fundamental assumption. So in layman’s terms if my sample is size 30 or larger, then the means of those samples will be normally distributed, (Salkind,2011).
What is a difference in a Type I and Type II error?
Type I error is when you reject the null hypnosis and there was really not any difference between the two groups, (Salkind,2011).
Type II error is when you accept the null hypnosis and there really are differences between the two groups, (Salkind,2011).
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