Applied Quantitative Methods: Analysis of Relationship between Flights and Baggage Sales, Contingency Table Probability

University
Applied Quantitative Methods
By
Your Name
Date
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 <Your Name> 2018

Question 2
Information about the number of flights at a given airport and the number of baggage’s sold is
provided to a manager. The manager needs to use the information to examine whether there
exists a relationship between the flights in the airport and the baggage’s sold, so that he keeps
more baggage’s in stock during busy hours of the airport in the upcoming holiday. A series of
questions is to be answered using the data as below:
Solutions
a. The data provided for the flights and the baggage’s is a sample. It is different from a
population in that, it uses old airport flight schedule to only indicate portion of the flights
recorded in the airport during a period of 7 weeks, and the number of baggage’s that were
sold during this period and when only the recorded flights were within the airport unlike
a population which would represent all the flights in the airport and baggage’s sold
during the period.
b. Since it is a sample the formula for standard deviation for a sample is applied as follows:
σ = √ ∑(x−μ)2
n−1
The x represents the value of flights, n is the sample size and μ represents the mean [1].
To simplify the process of, the data required for calculation of the standard deviation is
first simplified in table form as follows.
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 <Your Name> 2018

The standard deviation will be given by
¿ √ 151.43
6 =5.02
c. The interquartile range is the range the difference between the third quartile and the first
quartile [2]. To determine the interquartile range, the data is first arranged in ascending
order and the first (Q1), second (Q2) and third (Q3) quartiles determined. The data in
ascending order is as shown below:
Inter quartile range=Third quartile−First Quartile
Interquartile range=40−33=7
The interquartile range is more useful than standard deviation where the data is not
perfectly normally distributed because of outliers or because of being skewed [2]. For
example, where the baggage’s sold is 43 indicates that this is an outlier and therefore,
interquartile range would be more useful for analysis.
d. Coefficient of correlation is a value that indicates the strength and direction of linear
relationship between variables [3]. The relationship is strong positive if it approaches
positive one and strong negative if tit approaches the negative one. The calculation of the
coefficient of correlation “r” is calculated using the equation below:
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 <Your Name> 2018