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# Estimate on Quick brews weekly advertising expenditure

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Coffee Times weekly advertising expenditure, Coffee Times weekly advertising expenditure (lagged), Coffee Times price index, Coffee Times price index (Lagged), and Estimate on Quick brews weekly advertising expenditure (lagged).
The equation we have developed to predict effects on revenue when one or more of the independent variables is increased or decreased is:

Y = 246,491.990 + 4.556X1 - 699.171X2 + 5.719X4 - 624.925X5 - 1.729X6
Y = Predicted weekly revenue
X1 = Coffee Times weekly advertising expenditure
X2 = Coffee Times price index
X4 = Coffee Times weekly advertising expenditure (lagged)
X5 = Coffee Times price index (Lagged)
X6 = Estimate on Quick brews weekly advertising expenditure (lagged)

The local management can now use this model to make decisions regarding advertising and pricing while better understanding how Quick Brew's advertising expenditures will impact CoffeeTime revenues.

The analysis showed that the correlation between Coffee Times weekly advertising expenditure (lagged) and the Estimate on Quick brews weekly advertising expenditure (lagged) was fairly high at 0.65. However, since we determined to base our decision to remove any independent variables with correlations higher than 0.70, we will not remove any of them.
Before launching any type of product, it is extremely beneficial for businesses to find out if there is a need or a want for the product. Since Coffee Time's successful launch of their Coffee shop in India, they have decided to introduce a new product to increase sales and profits and would like to establish a want of 30% or more for the product to make it cost effective to launch.
In order to determine if 30% of India's population proportion would like the new sandwich, CoffeeTime has used a hypothesis and a Z-test to resolve this argument. Below you will find the hypothesis used, and other variables,
Ho: P&#8804;0.30 Level of significance: 20% or 0.20
H1: P>0.30 Type of test: Z-test / one tailed test
Sample size: 160 Z= -1.656
Critical Value Z= .84 Accept the null hypothesis

What can be determined from this hypothesis?