3. You would like to determine if there is a statistical relationship between the amount of caffein in a cup of coffee and their sales at their coffee franchises. The data is included in the set "Coffee by the Cup". Here is information about the variables. Variable Units Measurement Amount of caffeine in one cup Caffeine Milligrams Cups Sold Number of cups of the coffee Cups sold sold at all of the franchises a. Which variable is the explanatory variable and which variable is the response variable? b. Construct a scatterplot of the data. Based upon the scatterplot is there a linear relationship between the amount of caffeine in one cup of the coffee and the number of cups of coffee sold? Justify your reasoning using the scatterplot. c. Run a t-test for correlation using technology. Make sure you include the p-value and the printout. According to the t-test, is there a statistical relationship between the amount of caffeine in a cup of coffee and the number of cups sold? Justify your reasoning using the results of the test.

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Help with A., B.,C.

3. You would like to determine if there is a statistical relationship between the amount of caffein in
a cup of coffee and their sales at their coffee franchises. The data is included in the set "Coffee
by the Cup". Here is information about the variables.
Variable
Measurement
Amount of caffeine in one cup
Units
Caffeine
Milligrams
Cups Sold
Number of cups of the coffee
Cups sold
sold at all of the franchises
a. Which variable is the explanatory variable and which variable is the response variable?
b. Construct a scatterplot of the data. Based upon the scatterplot is there a linear relationship
between the amount of caffeine in one cup of the coffee and the number of cups of coffee
sold? Justify your reasoning using the scatterplot.
c. Run a t-test for correlation using technology. Make sure you include the p-value and the
printout. According to the t-test, is there a statistical relationship between the amount of
caffeine in a cup of coffee and the number of cups sold? Justify your reasoning using the
results of the test.
Transcribed Image Text:3. You would like to determine if there is a statistical relationship between the amount of caffein in a cup of coffee and their sales at their coffee franchises. The data is included in the set "Coffee by the Cup". Here is information about the variables. Variable Measurement Amount of caffeine in one cup Units Caffeine Milligrams Cups Sold Number of cups of the coffee Cups sold sold at all of the franchises a. Which variable is the explanatory variable and which variable is the response variable? b. Construct a scatterplot of the data. Based upon the scatterplot is there a linear relationship between the amount of caffeine in one cup of the coffee and the number of cups of coffee sold? Justify your reasoning using the scatterplot. c. Run a t-test for correlation using technology. Make sure you include the p-value and the printout. According to the t-test, is there a statistical relationship between the amount of caffeine in a cup of coffee and the number of cups sold? Justify your reasoning using the results of the test.
252
(Back
Coffe he Cp.c
ng of Cane Cups Sold
155
1215
200
131
175
235
1900
247
1750
258
1427
180
280
205
750
2100
178
256
1500
1670
290
2000
199
1233
200
1400
Transcribed Image Text:252 (Back Coffe he Cp.c ng of Cane Cups Sold 155 1215 200 131 175 235 1900 247 1750 258 1427 180 280 205 750 2100 178 256 1500 1670 290 2000 199 1233 200 1400
Expert Solution
Step 1

a) The explanatory variable is the amount of caffeine in a cup of coffee.

The response variable is the number of cups sold.

Step 2

b)Scatter plot:-

Statistics homework question answer, step 2, image 1

There is a linear relationship between the amount of caffeine used in a cup of coffee and the number of cups are sold.

As the amount of caffeine used in coffee increases, the number of cups sold also increases.

Step 3

3) The output of technology (Excel) is,

SUMMARY OUTPUT                
                 
Regression Statistics                
Multiple R 0.805952132              
R Square 0.649558839              
Adjusted R Square 0.622601827              
Standard Error 330.1318079              
Observations 15              
                 
ANOVA                
  df SS MS F Significance F      
Regression 1 2626161.796 2626162 24.096099 0.000285601      
Residual 13 1416831.137 108987          
Total 14 4042992.933            
                 
  Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -821.158967 445.6268592 -1.84271 0.088288065 -1783.877266 141.5593 -1783.88 141.5593
mg of caffine 9.478041349 1.930835298 4.908778 0.000285601 5.306725291 13.64936 5.306725 13.64936
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