UNIVERSITY EXAMINATIONS: 2017/2018
EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN
INFORMATION SYSTEMS MANAGEMENT
MISM5105 PRINCIPLES OF DATA SCIENCE
DATE: AUGUST, 2018 TIME: 2 HOURS
INSTRUCTIONS: Answer Question One & ANY OTHER TWO questions.
QUESTION ONE [20 MARKS]
a) Describe how you can turn unstructured data into structured data? 3 Marks
b) Nearly 80% of data analysis is spent on the cleaning and preparing data. Explain. 4 Marks
c) Which is the next step performed by data scientist after acquiring the data? Explain your
answer.
3Marks
d) Differentiate between Data visualization and data formating as used in big data analytics
4Marks
c) Assuming height and weight are available as a regular python lists,Write code that
imports numpy as np, and stores both the height and weight of the MLB players
as numpy arrays 3 Marks
d) Subsetting can be used to select and exclude variables and observations. Explain 3 Marks
QUESTION TWO [15 MARKS]
a) What is an outlier? Explain how you might screen for outliers and what you would do if you
found them in your dataset. Also, explain what an inlier is and how you might screen for
them and what you would do if you found them in your dataset. 4 Marks
b) i) In what phase of an anlytics project would you expect to invest most time and why ?
4 Marks
ii) Differentiate between Data Science , Machine Learning and AI. 3 Marks
iii) Describe the general syntax for calling functions and saving the result to a variable using
python . 4 Marks
QUESTION THREE [15 MARKS]
a) Discuss Recommender Systems as used today 6 Marks
b) Describe the main components of hadoop 2 Marks
c) Why is the role of data cleaning in data analysis? 3 Marks
d) Describe how big data analytics can be used to improve health services in Kenya 4 Marks
QUESTION FOUR [15 MARKS]
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 above 15 Marks
