Statistics Project

The project has several components: 
1) Forming a research question and stating the question as a claim to be analyzed with a hypothesis test. 
2) Collecting the appropriate data, and presenting it graphically. 
3) Calculating the various descriptive statistics necessary to describe the data and using them to carry out the hypothesis test. 
4) Presentation of your research on a poster and a brief talk. 
Component Details 
1) The forming of your research question will be the key element that will determine what data you will collect. The hypothesis test will be created directly from your claim. Here are examples of the typical form a claim can take: 
a) The mean value μ of a population is >, <, or ≠ to some value. 
b) The variance σ 2 or standard deviation σ of a population is value. >, <, or ≠ to some 
c) The proportion p of some quantity in a population is >, <, or ≠ to some value. 
d) The mean of one population μ1 is >, <, or ≠ to the mean of another population μ2 . 
e) The mean of the difference of paired data is >, <, or ≠ to some value. 
(An example of paired data could be the before and after cholesterol values of people given a cholesterol-lowering drug.) 
f) The variance of one population σ 2 is >, <, or ≠ to the variance of another population σ 2 
g) The proportion p1 of something in one population is >, <, or ≠ to the proportion p2 of something in another population. 
You may only choose among a, b, d, e, f, and g for your project. NOT c
2) Collecting your data should be the fun part of the project. Most of the hypothesis tests we study require that more than 30 values must be taken in your sample; some tests require that the data be normally distributed. Try to choose data that can be measured accurately and fairly quickly, such as length measured with a ruler or measuring tape, or weight measured with an accurate bathroom scale or postal or food scale. An accurate thermometer might be employed to measure temperature. You might come up with other quantities you can measure as well. 
On your poster, present the data in the following ways: 
i. A table of your data values. ii. A histogram of your data. 
iii. A normal quantile plot of your data (see section 6-7) using StatCrunch. 
(If your hypothesis test involves comparing samples from two populations make a table, histogram, and normal quantile plot for both sets of sample data.) 
3) Your poster should include a brief written description of your research and the equations, tables, and graphs that explain what you’ve done. 
You must include on your poster: 
a) Your claim 
b) Your null and alternate hypothesis 
c) A neat hand drawing of the appropriate distribution for your hypothesis test showing the tail(s) and the critical value(s) for a traditional hypothesis test (state the significance level). Do not use technology to draw this. 
d) The equation you used for the test statistic and the test statistic’s numerical value and associated p-value (use technology to get the p-value, not the approximate methods using the tables) 
Also, be sure to give the values of the descriptive statistics needed to compute the test statistic. 
e) The conclusion of your hypothesis test (for the null hypothesis and your claim)
Note: You may expand upon this list if you wish, but the list is the bare minimum of what must be on the poster. You should type up the text and equations (Microsoft Word has a decent equation editor). If you cannot type up the equations, they should be written neatly. The font sizes for text and equations should be large enough to be easily readable from several feet away.


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