The Study!
To
obtain the sample I sat in my truck outside of fast food places
and observed the sex of the people who pulled in and either
drove through or walked into the restaurant. The sample size for
each restaurant was the first 40 people the go to the restaurant
starting at 4 o’clock. The population of interest in this case
is all the people who go to fast food in a typical suburban city
like
The population in our study is all the people in north Olmsted who have consumed fast food.
Our null hypothesis is that there is a relationship between sex and fast food consumption.
Our alternative hypothesis is that there is no relation between sex and fast food consumption.
The significance level we used was a 0.05 alpha
For our study we decided to use a chi squared test because it is the easiest way to compare tests that have to do with seeing trends in male and female. The most common use for the chi squared test is to determine a goodness of fit test that compare two observations. Our study took observations of sex of people who consumed fast food and we desired to find the result of the difference between sex and fast food consumption.
Chi-Square
Test: Male, Female
Expected counts are printed below observed counts
Chi-Square contributions are printed below expected counts
Male Female
Total
1
20
20
40
21.40
18.60
0.092
0.105
2
25
15
40
21.40
18.60
0.606
0.697
3
17
23
40
21.40
18.60
0.905
1.041
4
26
14
40
21.40
18.60
0.989
1.138
5
19
21
40
21.40
18.60
0.269
0.310
Total
107
93
200
Chi-Sq = 6.150, DF = 4, P-Value = 0.188
