mkt202

After reading all the data, I first plan to make the form of Gender Ttest first. Here are all the steps I took to make this form.

T test

0.542771

The first step I did was copy and paste the “Eat Frequency” column from the datasheet. Step 2 Copy and paste the gender column. Step 3 Click on column B, then click on the top right corner of the Sort-AZ button. The fourth step copies all meal frequencies to the side of 0 and places them under the “female” column. Step 5 Copy the frequency next to 1 and paste it under the "Men" column. Step 6 Enter = Ttest and highlight the Make and female columns, and finally 2, 2. The last step is to analyze - if it is greater than .05, it means that it is not statistically significant. Therefore, when men and women eat the same food, they will not be positioned by gender.

The second step shows Race Avona. The following steps are the steps to make this form.

SUMMARY
Groups	Count	Sum	Average	Variance
other	69	233	3.376812	2.385337
B	69	253	3.666667	3.843137
w	69	230	3.333333	2.401961
h	69	264	3.826087	3.204604

Step 1 Copy the Eat frequency to column A.

Step 2 Copy Race to column B and sort

Step 3 Copy the frequency next to 1 and paste it under white

Step 4 does the same thing for AA, his. Oth - make sure to know the number of each race 1 = white, 2 = his, 3 = AA, 4 = Oth

Step 5 for one-way analysis of variance

Step 6 analyzes as before

The chi square test shown in the third table, the following steps are the steps to make this table.

	OBSERVED
	tp	bb
male	210	95	305
female	201	100	301
Totals	411	195	606
	Expected
	tp	bb
male	207	98
female	204	97
	Female TP	Male TP
1	91	98
2	110	112
Totals	201	210
	male bb	female bb
3	53	54
4	30	39
5	12	7
Totals	95	100

Step 1 Copy the "Outing Meal" column to column A.

Step 2 Copy the "Gender" column to column B

Step 3 sort by column B

Step 4 See the table to the right, create the table using the countif formula - just click on each cell to see the formula

Step 5 uses the totals in the table to create the "Observed" table above - view the colors to see where to go

Step 6 Create an expectation table by clicking each cell and following the formula

Step 7 executes ChiSquare by typing = ChiSquare, the first array will be just the number NO TOTALS

TB and BB are lower than expected

Step 8 analyzes as before

The last step shows Regression, the following steps are the steps to make this form.

Soup & Burrito	Soup & Deli	negative correlation
SUMMARY OUTPUT	SUMMARY OUTPUT	statistically significant
Regression Statistics	Regression Statistics	Regression Statistics
Multiple R	0.159883	Multiple R	0.065589	Multiple R	0.358779
R Square	0.025563	R Square	0.004302	R Square	0.128722
Adjusted R Square	0.023949	Adjusted R Square	0.002653	Adjusted R Square	0.12728
Standard Error	1.682902	Standard Error	1.701162	Standard Error	1.59133
Observations	606	Observations	606	Observations	606

Step 1 Copy and paste all 5 columns of pizza-hot dogs into the new table

Step 2 Go to the regression under Data Analysis - because your Y will be the Pizza column and X will be one of the other columns - you will have 5 different regression graphs

Step 3 Make sure to click on the label and output range

Step 4 Analysis - For your project, you are trying to determine if people are eating any of these other products with pizza, so statistically, sig pvalue means it really matters, then negative correlation People don't eat burritos and pizza