Analytics Project: Regression Model for Revenue and Site Selection

This analytics project focuses on developing a regression model to analyze the revenue of Prancing Ponies, considering factors like local income, competition, and location. The analysis reveals a significant relationship between these variables and revenue, with a 61% correlation and a 37% impact on the dependent variable due to changes in independent variables. Competition is found to have a lesser impact on revenue compared to local income and location. Furthermore, the project recommends Site B for business expansion based on lower competition, the potential for an experienced manager, and lower fixed costs, despite a slightly lower per capita income compared to Site A. Desklib provides access to this and other solved assignments for students.

Analytics Project

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
CONCLUSION................................................................................................................................3
REFERENCES................................................................................................................................4

PART 1
A. Developing regression model for revenue
Regression Statistics
Multiple R 0.613353803
R Square 0.376202887
Adjusted R
Square 0.332682159
Standard Error 0.537689551
Observations 47
ANOVA
df SS MS F
Significance
F
Regression 3 7.497395368 2.499131789 8.644223059 0.000132585
Residual 43 12.43173229 0.289110053
Total 46 19.92912766
Coefficients
Standard
Error t Stat P-value Lower 95% Upper 95%
Lower
95.0%
Upper
95.0%
Intercept 2.06243619 0.580611877 3.552177056 0.000941599 0.891520746 3.233351634 0.891520746 3.233351634
LocalIncome -0.04790613 0.02250715 -2.12848485 0.039066942 -0.09329612 -0.00251613 -0.09329612 -0.00251613
Competition 0.039101285 0.026923271 1.452322993 0.153670189 -0.01519466 0.093397235 -0.01519466 0.093397235
Location 0.24497721 0.059160178 4.140914033 0.000158501 0.125669341 0.364285079 0.125669341 0.364285079
With the help of the above analysis it is clear that there is a relation being present in the both the variables. This is particularly
because of the reason that revenue of the company is being affected by the different variables. These variable involves local income,
competition and location. This is particularly because of the reason that all these factors affect the revenue of Prancing Ponies. The

significance value is 0.0001 which is lower than the standard that is 0.05. hence, with this it can be stated that there is a relation being
present in revenue and other factors (Desboulets, 2018). Along this this, R is 61 % which implies that there is 61% of correlation
between both the variables. Moreover, the R square is 37% which states that there will be a change of 37 % within the dependent
variable because of change in independent variable. Further with the analysis it was evident that competition is the factor which not
affects the revenue of company. The reason underlying this fact is that it is having the P value of 0.1537 which is greater than standard
that is 0.05. Hence, the competition does not affect the revenue to a great extent but local income and location affect the working.
B. Recommendation for selection of one business choice
With the comparative analysis of both the options that is site A and B, it is recommended to Prancing Ponies that they must go
for Site B. The reason underlying selection of this site is that the place is already a restaurant and the competition within the nearby
place is also low. In case of Site A there is 9 restaurants in 2 miles’ distance but in case of site B there is only 2 pubs in 2 miles’
distance. Along with this, another reason for recommending site B is that in case the experienced manager of other chain will be
located then this will beneficial for company (Ulbrich, 2020). This is because of the reason that the highly experienced manager will
provide better guidance and will manage the place in good manner. Moreover, the fixed cost of site B is £1.1 million but site A is £1.5
million which is more. The only drawback of the site B project is that the per capita income of the area is £26000 per annum but for
site A is £32000 per year which is more. But site B option is having other benefits more which makes is a viable project to invest.

REFERENCES
Books and Journals
Desboulets, L. D. D., 2018. A review on variable selection in regression analysis. Econometrics. 6(4). p.45.
Ulbrich, F., 2020. Project Selection: Picking the Best Option. SAGE Publications: SAGE Business Cases Originals.