Statistics for Pre-MSc Assignment
Online Sales & Product Returns
Almost everyone buys products online nowadays. Whether and how much a customer
buys online will depend on various factors. In addition, the bad news for online
retailers is that oftentimes (some of) these purchases are returned to the retailer.
Product returns impose a substantial cost for online retailers. Product returns not only
result in lost sales, but also lead to other costs such as shipping fees, often paid by the
retailer, and remanufacturing costs such as repackaging the product. Traditionally,
management deals with “selling products to consumers”, but one should probably
examine and manage online purchases ánd product returns.
For this Statistics assignment, a (small) part of the customer database of a retailer is
available. The retailer sells shoes for females and males and several related product
categories, both online and offline. This database contains only the online purchases,
not the offline purchases. It would be interesting to examine factors related to online
purchases and product returns (both potential dependent variables). The explanatory
variables could be grouped into:
● customer characteristics (e.g. age, gender);
● characteristics of the basket (e.g. number of items, value);
● characteristics of the specific product (e.g. product category, style, price,
discount).
The customer database contains more than 7000 items that have been purchased. Of
course, the number of baskets/orders is smaller; each row in the database refers to a
specific product. In a few cases, multiple identical items have been ordered, which are
presented on the same row. The database can be obtained by contacting your tutorial
supervisor.
The assignment is to examine the drivers of online purchases and product returns. To
obtain such insights, almost all statistical methods discussed throughout the course
Statistics for the Pre-MSc can and should be used. It is not needed to conduct and
report “100s of t-test”, but one is expected to perform descriptive and inferential
statistics (cross-tabulations, correlations, t-test, F-test, regression).
The assignment can be done by groups of max 3 students, identified on the front page
of the report. The written report should have max 10 pages, including all tables, etc.
The report should not simply be a list of SPSS output, but an actual report with a short
introduction and, more importantly, interpretations of the results and some
conclusions. It has to be handed in through BrightSpace, before Thursday December
22, 6PM.
Online Sales & Product Returns
Almost everyone buys products online nowadays. Whether and how much a customer
buys online will depend on various factors. In addition, the bad news for online
retailers is that oftentimes (some of) these purchases are returned to the retailer.
Product returns impose a substantial cost for online retailers. Product returns not only
result in lost sales, but also lead to other costs such as shipping fees, often paid by the
retailer, and remanufacturing costs such as repackaging the product. Traditionally,
management deals with “selling products to consumers”, but one should probably
examine and manage online purchases ánd product returns.
For this Statistics assignment, a (small) part of the customer database of a retailer is
available. The retailer sells shoes for females and males and several related product
categories, both online and offline. This database contains only the online purchases,
not the offline purchases. It would be interesting to examine factors related to online
purchases and product returns (both potential dependent variables). The explanatory
variables could be grouped into:
● customer characteristics (e.g. age, gender);
● characteristics of the basket (e.g. number of items, value);
● characteristics of the specific product (e.g. product category, style, price,
discount).
The customer database contains more than 7000 items that have been purchased. Of
course, the number of baskets/orders is smaller; each row in the database refers to a
specific product. In a few cases, multiple identical items have been ordered, which are
presented on the same row. The database can be obtained by contacting your tutorial
supervisor.
The assignment is to examine the drivers of online purchases and product returns. To
obtain such insights, almost all statistical methods discussed throughout the course
Statistics for the Pre-MSc can and should be used. It is not needed to conduct and
report “100s of t-test”, but one is expected to perform descriptive and inferential
statistics (cross-tabulations, correlations, t-test, F-test, regression).
The assignment can be done by groups of max 3 students, identified on the front page
of the report. The written report should have max 10 pages, including all tables, etc.
The report should not simply be a list of SPSS output, but an actual report with a short
introduction and, more importantly, interpretations of the results and some
conclusions. It has to be handed in through BrightSpace, before Thursday December
22, 6PM.
