Data Analytics for Management

We have Data Analytics Project which is related to Descriptive , Regression Analysis and Hypothesis Testing. Attached is the exam with the excel backup. please answer the questions. follow the guidance in the PDF

Requirements: per guidance in PDF

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Ali Aouad
EMBA Dubai CD24 Spring 2021
Data Analytics for Management
Final Exam, Individual Assignment
Instructions:
This assignment counts 50% of your total grade. The assignment consists of THREE questions, with a total grade of 100 points. Please note that you need a minimum of 50 points out of 100 in order to pass the course. TWO data files for the assignment are uploaded on LBS Canvas.
Please read and answer all the questions. Please communicate clearly all the steps that lead to the answer of each question. Please submit only ONE .doc (.docx) or .pdf file with the answers to all questions. Excel files will NOT be accepted for submission. Excel outputs should be copied and pasted on the .doc or .pdf file if needed.
This is an individual assignment, which means that you should not consult with anyone. If you have any clarifying question, please email [email protected].
The report is due by 9:00PM (GST) on Sunday March 14 2021. Please submit a softcopy of your report via LBS Canvas1 under Assignment — Final Exam.
To ensure fairness, late submissions (except for Extenuating Circumstances approved by the Program Office) will not be accepted.
1 If you experience any last minute problems with Canvas, please send the assignment to [email protected] by the due date and time. If the submission is successful, please do NOT email the assignment.
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1. (30 points) Mark each statement as TRUE or FALSE. Justify your answers.
a) (6 points) Paul, a venture capitalist, is considering to invest in local start-ups, but he needs to
ensure an average yearly return-on-investment (ROI) of at least 3%. He has acquired a dataset
showing that the average ROI for similar investments is of 5%. His dataset is comprised of 64
observations. Paul concludes that he does not need to build a confidence interval.
b) (6 points) The Dubai Hospital generally expects 10 patients per day who require urgent care,
on average. In the past 100 days, the data shows that there are on average 10 urgent cases
per day, with a standard deviation of 10. The number of urgent cases has significantly
deviated from the expectation of the hospital, at the 5% significance level.
c) (6 points) You are considering a potential investment opportunity in a hedge fund. You are
given access to the historical monthly returns since the inception of the fund. To be on the
safe end, you should remove all the outliers.
d) (6 points) There is no relationship at the 5% significance level between the consumption of
coffee per resident (target variable) and the price of real-estate (explanatory variable) in a
data set formed by the 100 largest cities in the world. This means that higher real-estate
prices cause a higher consumption of coffee, OR, vice versa, a higher consumption of coffee
causes higher real-estate prices; however, we cannot conclude about the direction of
causality.
e) (6 points) You are testing a new page layout for your brand’s website. You run an A/B
experiment hoping to see an increase of purchases from customers landing on the new
webpage. Unfortunately, the A/B test does not show any statistically significant change in the
customers’ purchase rate (5% significance level). You should repeat as many A/B tests as
required until observing a statistically significant change in the purchase rate.
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2. (35 points) Regression: Hakim is the CEO and co-founder of Vatler, a start-up providing ondemand
parking services through a mobile application. Parking is increasingly difficult and timeconsuming
in Dubai downtown, particularly in the evening on week-ends. Through Vatler’s
application, users can request a valet to meet them in any given location; the valet will find a
parking spot, and the car is returned to the user by the same valet whenever she needs her car
back. Hakim’s team is testing the application in two regions of Dubai, in the downtown area. Every
Friday evening, the valets are deployed in these regions and the service is available from 7pm until
10pm. While the app has been successful thus far, the team struggles with basic operational
decisions. As noted by Hakim: “We have been over-spending to reserve parking spots and onboard
more valets to the platform. How many valets and parking spots do we really need to maintain a
service of good quality?”. His co-founder Jennifer stresses out the importance of keeping the waittimes
low: “If we don’t have enough valets, we won’t have a good coverage, users will have to
wait longer, and valets will waste a lot of time to get to the users! We should target a wait-time
below 5 min.”. In this exercise, the goal is to build a linear regression model to predict the waittime
as a function of the number of reserved parking slots and the number of valets.
a) (10 points) Construct a linear regression model that predicts the wait-time (dependent
variable, Column G) as a function of the number of valets (independent variable, column C)
and the number of parking slots (independent variable, column D). Hakim and Jennifer believe
that the number of valets matters more than the number of reserved parking slots. Is their
intuition correct? What variable(s) should be kept in the linear regression model?
b) (10 points) To be more precise and granular, Jennifer can distinguish two types of valets:
licensed and unlicensed. Licensed valets have followed a special training, and they can park
cars in various areas which are not accessible to regular drivers. Construct a linear regression
model that predicts the wait-time (dependent variable, column G) as a function of the number
of licensed valets (independent variable, column E) and the number of unlicensed valets
(independent variable, column F). Are licensed valets more effective than unlicensed valets to
reduce the wait-time?
c) (8 points) Using the regression model constructed in question (b), are you 95% confident that
the wait-time won’t exceed 5 min if the start-up hires 20 licensed valets and 25 unlicensed
valets?
d) (7 points) Jennifer is looking into how the linear regression of question (b) can be further
improved. She believes that the benefit from hiring one extra valet diminishes as the number
of valets (licensed or unlicensed) increases: “Looking at the residual plots, I suspect that there
are non-linear dependencies between the wait-time and the numbers of licensed and
unlicensed valets”. How can the independent variables be transformed to reflect this
observation in the linear regression model? Construct a new linear regression following this
transformation.
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3. (35 points) Hypothesis Testing: Jennifer is the founder of a chain of restaurants in Paris and Dubai,
specialized in high-quality gourmet burgers. The restaurant chain is notorious for an awardwinning
premium burger meal, known as the “CHEF Burger”. Jennifer has reviewed recent sales
data in her restaurants. She noticed a drop in the number of orders for the CHEF burger meals.
She is very concerned that the recent data signals that customers have lost interest in her flagship
meal. The goal of this exercise is to help her figure out whether there is a change in the demand
pattern.
a) (10 points) Jennifer would like to test if the aggregate number of CHEF meal orders has
decreased in 2019 compared to previous years (2018 and 2017) across all cities. Formulate
and conduct the corresponding two-sample hypothesis test. Has the number of CHEF meal
orders significantly changed in 2019 compared to previous years, at the 5% significance
level?
b) (10 points) While aggregate sales seem unchanged, the CFO of the firm has observed that the
financial performance in Paris has sharply declined the past year. Based on this observation,
Jennifer would like to conduct an additional hypothesis test by considering CHEF meal orders
in Paris only. Formulate and conduct the corresponding two-sample hypothesis test. Has the
number of CHEF meal orders significantly changed in Paris in 2019 compared to previous
years, at the 5% significance level?
c) (10 points) Conduct a similar analysis for the number of BIG meal orders in Paris only.
d) (5 points) Based on answers to questions (b)-(c), what can you infer about the changes in
the demand patterns in Paris?

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