PROJECT REPORT;INTRODUCTION TO STATISTICS
Calculate the pair-wise correlation coefficients between sales per square meter and
each of the other variables and test their statistical significance. Produce scatter
plots for each pair of variables. Provide a written interpretation for each of the
correlation coefficients and the related scatter plots
INTRODUCTION TO STATISTICS – (L1025)
The report should be 2,000 words in length and must be word-processed. Projects that exceed this word limit will be penalised.
The exercise should be treated as an exercise in report writing, not just a statistical exercise. You should pay a good deal of attention to structure and to ensuring that the main results from the exercise are clearly reported. A report that neglects the issues and just goes through statistical techniques in a mechanical manner will be penalised. You therefore need to think clearly about the issues that you are examining and layout your hypotheses and findings carefully.
Please note that you have to include in your report graphs and tables (they do not count for number of words). You have to clearly present tables and graphs, with appropriate labels and full explanations. Tables and Graphs should be numbered with self-explanatory headings. Rows and columns and graph axes must be labelled.
Marks will be lost for poor spelling and grammar, and for poorly presented work.
Collaboration and group work are NOT permitted on this project!
Deadline for Submission
4:00pm Thursday 9th April
There are penalties for late submission, which are set out in the Handbook for Candidates.
The dataset available on Study Direct contains annual sales data and other characteristics of 400 Dutch fashion stores in 1990. The following variables appear in the data set:
Sales per square metre
Number of full-timers
Number of part-timers
Total number of hours worked
Sales floor space of the store (in square metres)
1) Calculate the pair-wise correlation coefficients between sales per square meter and each of the other variables and test their statistical significance. Produce scatter plots for each pair of variables. Provide a written interpretation for each of the correlation coefficients and the related scatter plots.
2) Write down an equation representing a linear regression model in which sales per square metre depend on a constant, the total number of hours worked and floor space of the store (in square metres). Estimate the equation, report the results, and comment on the overall goodness of the model.
3) Interpret the estimated coefficients from an economic perspective and comment on their statistical significance.
4) Does the inclusion of the number of full-timers and part-timers significantly improve the model?