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Project - Essay Example

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The diagram above shows the scatterplots for the consumption of coffee and sodas over a period of 48 days. From the diagram we wtiness that the consumption of coffee was steady for the first twenty days before it picked in between the 21st to the 24th days. In the case of…

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Download file to see previous pages From the regression model we get to know that 42% of the data fits the goodness of fit test. Therefore, we can conclude that time used in this dataset does not represent or affect the consumption of sodas.
The figure below shows the results of the regression model conducted on the consumption of coffee over a 48 day period. From the regression model get to know that 52.8% of the variation in consumption of coffee is explained by time (Lawrence 321). This is obtained from the R square value.
3. From the analysis of the regression model, we notice that both trends are negative and therefore, there is little relation between time and the consumption of either coffee or sodas. The R squared values are low since there exists no relation between the variables and the change in time does not affect the consumption of either coffee or sodas.
4. From the analysis and investigation of the data on the consumption of coffee or sodas, we come to notice that the average daily temperature affect the consumption of coffee and sodas. When the average daily temperature increases then the consumption of sodas increase while that of coffee decreases and the same occurs vice-versa (Lawrence 85).
From the correlation analysis conducted above, we get to know that the variable sodas and coffees have little correlation since the value is -0.38. Thus no correlation exists while the correlation between sodas and the variable Max. Daily Temperature is positive standing at 0.52. On the other hand there is a negative correlation between coffees and Max. Daily temperature.
6. When the two variables sodas and coffees are combined we come up with a variable known as total soda and coffee. The p value for this variable is 0.82 and this is a positive trend for the sale of the drinks. From a business perspective, we can analyse and conclude that there is an increase in sales when the two variables are combined (Berk 106).
8. The model that we get when a multiple regression ...Download file to see next pagesRead More
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