Reference no: EM132519788 , Length: word count:1500
SG4011 Business Statistics and Data Analysis - University of East London
Assignment-Data Analysis and Forecasting
Background:
You are working in sales for AutoMobile Inc., a firm of car distributors, who are thinking of expanding into a new market. You have been asked to investigate the factors which determine vehicle ownership in various European countries; the most recent data you can find is for 2018, and is as shown in Cars2.xls.
To prepare for a presentation to management about opportunities for sales in Turkey, carry out the following steps:
a.) Plot scatter graphs of vehicles per thousand population against income, population, population density and percentage of population in urban areas in the Excel file with which you believe there might be correlation. What do your results suggest?
b.) For the variable which is more closely correlated to vehicles per thousand population, calculate the equation of the regression line, and interpret the results.
c.) Plot scatter graphs of total vehicle ownership against population, population density per km^2 and population in urban areas. What do these graphs suggest?
d.) For the variable which is more closely correlated to total vehicle ownership, calculate the equation of the regression line and interpret the results.
e.) Which of the two regression equations do you think will be more useful to the company?
f.) Data for Turkey is as follows:
Income
|
Population
|
Population density
|
% urban
|
6.1
|
67
|
90
|
67
|
Use this data and the regression equations calculated in b.) and d.) above to predict the total number of vehicles and number of vehicles per 1000 population for Turkey. The actual figures are 6.4 million and 96 per 1000 population. Explain why your predictions differ from these values.
Attachment:- Data Analysis and Forecasting.rar