Falling Profits in Londons Dodo Supermarket - Essay Example

The independent variables on the other hand include; Workers, Population Density, Average Income, Products, Price Levels, Competition, Service Ratings, Location (Central London), and Convenience.
Consider the Regression Model Summery table below;

a. Predictors: (Constant), Convenience, workers, Average Income, Competition, Service Rating, Price Level, Products, Central London, Population Density
b. Dependent Variable: profit

According to the table above, the R Square and the Adjusted R square are above 50%, 0.652, and 0.564 suggesting that they are 65.2% and 56.4% respectively. This means that 56.4% of the independent variables explain the dependent variable (profit levels).
The table below shows the summary statistics table that reflects the relationship between profits and workers:

a. Multiple modes exist. The smallest value is shown

This can be well illustrated in the scatter plot shown below:

The frequency table below illustrates the frequency distribution of the profit level of the supermarket.

The frequency table below also shows the frequency distribution of profits per worker in the Dodo Supermarket.

Autocorrelation Analysis
The Durbin Watson value is 2.119, implying that the test is not conclusive (Don’t Know), considering the following:
i. Less than dL (< 1.14 ) = Positive autocorrelation
ii. Between dL and dU ( 1.14 and 1.74 ) = Test not conclusive ( Don’t Know )
iii. Between dU and 4dU ( 1.74 and 2.26 ) = No autocorrelation
iv. Between 4dU and 4dL (2.26 and 2.86 ) = Test not conclusive ( Don’t Know )
v. Greater than 4dU ( > 2.86 ) = Negative autocorrelation
Since the Durbin-Watson, the result indicates 2.119, a figure that represents no autocorrelation; therefore, the regression results are reliable and unbiased. The statistical result above can be used effectively in predicting the variations in the profit level at the supermarket group ‘Dodo’.

Walrus is an online bicycle store that sells mainly one product, their ‘tBike’. Another online bicycle store, ‘Shifty’, has recently announced a lasting and substantial reduction in their prices for the next year. The analysis below is aimed at determining whether this is likely to significantly affect their sales of bikes.
Analysis
According to the analysis below, tBike Sales are the dependent variable while shifty Price, Average Income, December, and tBike Price are independent variables. The table below summarizes the descriptive statistics.

The model summary below shows the variations and relationships between the dependent and independent variables. According to the table below, the adjusted R squared is 0.729 implying that 72.9% of the independent variables explain the variations of the dependent variable, like Sales throughout the data.

The table of coefficients summarizes the relationship model;

The relationship can also be illustrated using the histogram and the scatter diagram below:

Autocorrelation Analysis
The Durbin Watson value is 1.087, implying that the test is not conclusive (Don’t Know), considering the following:
i. Less than dL (< 1.14 ) = Positive autocorrelation
ii. Between dL and dU ( 1.14 and 1.74 ) = Test not conclusive ( Don’t Know )
iii. Between dU and 4dU ( 1.74 and 2.26 ) = No autocorrelation
iv. Between 4dU and 4dL (2.26 and 2.86 ) = Test not conclusive ( Don’t Know )
v. Greater than 4dU ( > 2.86 ) = Negative autocorrelation
Since the Durbin-Watson, the result indicates 1.087, a figure that represents no autocorrelation; therefore, the regression results are reliable and unbiased. The statistical result above can be used effectively in predicting the variations in the profit level at Walrus. Read More