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.
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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.
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SUMMARY |
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Groups |
Count |
Sum |
Average |
Variance |
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other |
69 |
233 |
3.376812 |
2.385337 |
|
B |
69 |
253 |
3.666667 |
3.843137 |
|
w |
69 |
230 |
3.333333 |
2.401961 |
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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.
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OBSERVED |
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tp |
bb |
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male |
210 |
95 |
305 |
|
female |
201 |
100 |
301 |
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Totals |
411 |
195 |
606 |
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Expected |
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tp |
bb |
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male |
207 |
98 |
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female |
204 |
97 |
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Female TP |
Male TP |
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1 |
91 |
98 |
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2 |
110 |
112 |
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Totals |
201 |
210 |
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male bb |
female bb |
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3 |
53 |
54 |
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4 |
30 |
39 |
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5 |
12 |
7 |
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Totals |
95 |
100 |
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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.
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Soup & Burrito |
Soup & Deli |
negative correlation |
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SUMMARY OUTPUT |
SUMMARY OUTPUT |
statistically significant |
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Regression Statistics |
Regression Statistics |
Regression Statistics |
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Multiple R |
0.159883 |
Multiple R |
0.065589 |
Multiple R |
0.358779 |
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R Square |
0.025563 |
R Square |
0.004302 |
R Square |
0.128722 |
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Adjusted R Square |
0.023949 |
Adjusted R Square |
0.002653 |
Adjusted R Square |
0.12728 |
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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