UNIVERSITY EXAMINATIONS: 2018/2019
EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN
INFORMATION SYSTEMS MANAGEMENT
MISM 5105: PRINCIPLES OF DATA SCIENCE
DATE: AUGUST, 2019 TIME: 2 HOURS
INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions.
QUESTION ONE
a) write code in python to create a lists carprices comprising cars and their prices of 10 cars.
3 Marks
i) Print out the list 2 Marks
ii) Add the price of first and last car in your list print the total cost 3 Marks
b) Differentiate between the following terms as used in big data analytics:
i) ELT and ETL 3 Marks
ii) classification and clustering 3 Marks
iii) Semi structured and quasi structured data 3 Marks
iv) Data exploration and data presentation 3 Marks
QUESTION TWO
Scenerio
A medium size retail bank in kenya wants to improve its net present value and its retention rate
of customers.They want to establish an effective market campaign targeting customers to
reduce the churn rate by at least 5%. They also want to determine whether those customers are
worth retaining. In addition the wants to analyze reasons for customer attrition and what they
can do to keep them. The wants to build a data ware house to support marketing and other
customer related care groups.
Required:
Perform an analytic plan for the bank above case study above15 Marks
QUESTION THREE
a) Discuss the benefits of doing a pilot program before a full scale roll out of a new
analytical methodology 6 Marks
b) Misusing charts tends to confuse the audience. Discuss this statement in the light of the
different type of charts and when best to use them. 9 Marks
QUESTION FOUR
You’ve contacted FIFA for some data and they handed you two lists. The lists are the
following:
positions = [‘GK’, ‘M’, ‘A’, ‘D’, …]
heights = [191, 184, 185, 180, …]
Each element in the lists corresponds to a player. The first list, positions, contains strings
representing each player’s position. The possible positions
are: ‘GK’ (goalkeeper), ‘M’ (midfield), ‘A’ (attack) and ‘D’ (defense). The second list, heights,
contains integers representing the height of the player in cm. The first player in the lists is a
goalkeeper and is pretty tall (191 cm).
You’re fairly confident that the median height of goalkeepers is higher than that of other players
on the soccer field. Some of your friends don’t believe you, so you are determined to show them
using the data you received from FIFA and your newly acquired Python skills
• Convert heights and positions, which are regular lists, to numpy arrays. Call
them np_heights and np_positions.
• Extract all the heights of the goalkeepers. You can use a little trick here:
use np_positions == ‘GK’ as an index for np_heights. Assign the result to gk_heights.
• Extract all the heights of all the other players. This time use np_positions != ‘GK’ as an
index for np_heights. Assign the result to other_heights.
• Print out the median height of the goalkeepers using np.median(). Replace None with
the correct code.
• Do the same for the other players. Print out their median height. Replace None with
the correct code. 15 Marks
