MBA Module 5
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Southern New Hampshire University *
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Business
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May 20, 2024
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MBA 504 Module Five PowerPoint Template
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[Date]
[Professor]
[Section]
Overview
A high correlation exists between advertising expenses and flavor rating, which can explain the high variance of Cookie Doug and Chocolate ice cream sales. This is because advertising expenses are directly related to brand recognition, which can influence consumer buying decisions. Companies that spend more money on advertising are more likely to have higher sales than those that do not.
Cookie Dough ice cream has a R2 of .99, or 99%, and a P-Value of 3892.57 relationship with advertising expenses. This means that the probability of Cookie Dough ice cream being a true positive is 99% and the probability of it being a false negative is 1%. The P-Value of 3892.57 is the probability of Cookie Dough ice cream being a true positive assuming the null hypothesis is true.
In the case of Chocolate ice cream, R2 is .99 or 99%, and the P-value is 761652.34. This means that the data is highly statistically significant. Therefore, it can be concluded that Chocolate ice cream is the preferred flavor over the rest.
Flavor One
The multivariate linear equation for Quantity Sold (dependent variable) and Advertising Expenses (independent variable) is y = -69.24 + 2.63 (Adv. Exp) - 1.16 (Flavor).
In the case of Cookie Doug Ice Cream, R2 = .99 indicates that 99% of its sales are explained by a combination of advertising expenses and flavor rating This tells us that advertising expenses have a significant impact on the sales of this ice cream. Flavor rating, on the other hand, has a relatively smaller impact. This suggests that the company should focus on advertising more than on flavor in order to increase its sales.
3. The P-Value is 3892.57, which indicates that the overall regression model is significant. There is a strong correlation between advertising expenses and Cookie Dough quantity. This means that when advertising expenses increase, the amount of Cookie Dough produced also increases. This is indicative of a positive relationship between the two variables, which suggests that the regression model is accurate and reliable.
Cookie Dough
Regression Statistics
Multiple R
0.99935837
R Square
0.998717151
Adjusted R Square
0.998460581
Standard Error
86.96194264
Observations
13
ANOVA
df
SS
MS
F
Significance F
Regression
2
58874267.07
29437133.54
3892.575566
3.47438E-15
Residual
10
75623.79468
7562.379468
Total
12
58949890.87
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
-69.24384817
119.053481
-0.581619685
0.57369911
-334.5115347
196.0238384
-334.5115347
196.0238384
Average of Advertising Expenses
2.635731491
0.02987223
88.23350345
8.55481E-16
2.569172015
2.702290967
2.569172015
2.702290967
Count of Flavor
-1.16984E-14
0.274281393
-4.26512E-14
1
-0.611137028
0.611137028
-0.611137028
0.611137028
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