Blog

This task was originally
in Norwegian, so I have translated the task from Norwegian to English. Message
me if I have translated this task wrong in any way ( only 4 tasks, and not master’s assignment, only for pumping up the price)
Background
The article “Sandwich analytics: A dataset
comprising one year’s weekly sales data correlated with crime, demographics,
and weather” by Spaulding et. eel. (2019) gives us an insight into sales
data from a fast food chain for 10 of their outlets in the USA.
You can find the article here: https://www.sciencedirect.com/science/article/pii/S2352340919306067#!
The data can be downloaded here: https://data.mendeley.com/datasets/6htjnfs78b/1
Background
You / your team is now employed as an analyst in ACME analytics. The company that “owns” the data has announced a tender competition. They want to develop a system that reports sales for all outlets in their group. The sandwich data should be used to show what you can deliver.
Tasks (Each task counts for 25% of the grade)
Task 1
The first

task is to write R code that merges the 6 datasets into one large dataset.
You must use the variables that the different datasets have in common to do this. This process must be briefly documented and commented on.
Task 2
The data will be used for a weekly sales report for a single sale. Give some examples of what the content of such a short-term individual report should contain. Justify your choices and the thinking behind the figures and any tables.
Task 3
The data will be used for a monthly sales report at an aggregate level to the group management. Give some examples of what the content of such a long-term group report should contain. Justify your choices and the thinking behind the figures and any tables.
Task 4
Can the data be used to plan new sales? If the group management wants to establish a new outlet, how can they use this data to find the best location?
(Message
from me:
I only want
the r-studio code done. I want to do the “word” writing and analyses myself, I
only want the coding from you.
-Best
regards Chris)