Business Decision Making Part Two QNT275 Descriptive statistics are used in the presentation of data sets in form of meaningful summaries. This helps for the important patterns of the data to be observable. Descriptive statistics may not be useful in drawing final conclusions about the data. These statistics are majorly used in describing quantitative data as they involve numerical calculations. The main descriptive statistics are the measures of central tendency and the measures of variability. Measures of central tendency express the central position of a data. Measures of variability, on the other hand, represent spread of the values in a data set. For the case of American Airline Group, the research involves both quantitative and qualitative data. The operational costs, which represent the dependent variable, can be understood by studying the operational changes that result from the merger. This includes quantitative data on the number of passengers that have access to the airline’s services. The descriptive statistics which could be used in summarized this data include the mean, mode, and median. The mean represents the average number of passengers using the airline’s services for a given period of time, for example in one day. The mode represents the most recurrent number in the data set. For example, if the data were to be collected for a period of one month, the particular number of passengers that would be recorded in many days would represent the mode of the data. Median, on the other hand, represents the centrally placed value after the data has been arranged in either an ascending order or descending order. Descriptive statistics could also be used for summarizing data on the financial capability of the merger. This data is obtained from a survey audit of the airline’s financial data. The measures of variability that could be used in this research include the range, variance, standard deviation, quartiles and absolute. These measures describe the consistency of data by presenting the variability (Holcomb, 2017). Inferential statistics involve making generalizations about the population using facts from the sample. These statistics are useful where the population under study is large. In this case, it is most feasible to select a small group to be a representative of the population. The inferential statistics that can be used in the analysis of the data from the American Airline Group merger include the estimation of parameters and tests of hypothesis. Estimation of parameters involves approximating population parameters using the calculated sample statistics. For example, the population mean may be estimated by the sample mean. It would be economical to study only a small group. Estimation of parameters is thus highly useful for making inferences about the whole population (Bernstein, & Bernstein, 2011). Test of hypothesis involves testing the accuracy of a claim about the population based on the sample under study. Othe ...

1. Business Decision Making Part Two
QNT275
Descriptive statistics are used in the presentation of data sets in
form of meaningful summaries. This helps for the important
patterns of the data to be observable. Descriptive statistics may
not be useful in drawing final conclusions about the data. These
statistics are majorly used in describing quantitative data as
they involve numerical calculations. The main descriptive
statistics are the measures of central tendency and the measures
of variability. Measures of central tendency express the central
position of a data. Measures of variability, on the other hand,
represent spread of the values in a data set.
For the case of American Airline Group, the research involves
both quantitative and qualitative data. The operational costs,
which represent the dependent variable, can be understood by
studying the operational changes that result from the merger.
This includes quantitative data on the number of passengers that
have access to the airline’s services. The descriptive statistics
which could be used in summarized this data include the mean,

2. mode, and median. The mean represents the average number of
passengers using the airline’s services for a given period of
time, for example in one day. The mode represents the most
recurrent number in the data set. For example, if the data were
to be collected for a period of one month, the particular number
of passengers that would be recorded in many days would
represent the mode of the data. Median, on the other hand,
represents the centrally placed value after the data has been
arranged in either an ascending order or descending order.
Descriptive statistics could also be used for summarizing data
on the financial capability of the merger. This data is obtained
from a survey audit of the airline’s financial data. The measures
of variability that could be used in this research include the
range, variance, standard deviation, quartiles and absolute.
These measures describe the consistency of data by presenting
the variability (Holcomb, 2017).
Inferential statistics involve making generalizations about the
population using facts from the sample. These statistics are
useful where the population under study is large. In this case, it
is most feasible to select a small group to be a representative of
the population. The inferential statistics that can be used in the
analysis of the data from the American Airline Group merger
include the estimation of parameters and tests of hypothesis.
Estimation of parameters involves approximating population
parameters using the calculated sample statistics. For example,
the population mean may be estimated by the sample mean. It
would be economical to study only a small group. Estimation of
parameters is thus highly useful for making inferences about the
whole population (Bernstein, & Bernstein, 2011).
Test of hypothesis involves testing the accuracy of a claim
about the population based on the sample under study. Other
inferential statistics applicable to this research are correlation
testing and regression analysis. These involve testing the
relationship between variables. They would be applicable in this
research to identify how the operating costs are related to the
financial capability of the merger. Inferential statistics can also

3. be used to analyze qualitative data. The qualitative data
collected in this study include customers’ opinions on how the
new airline merger has changed their choice of travel. A
positive correlation between the operating costs and financial
capability would imply that the merger, which has a higher
financial capability compared to the individual companies,
would have eased airline operations. This can be explained by
the introduction of high-capacity planes as well as cost-efficient
fuel (Bernstein, & Bernstein, 2011).
Inferential statistics involve estimation of population parameter
using the selected sample. This means that the results are not
always 100% accurate. Inferential statistics involve probability.
The population parameters are estimated to lie within a given
confidence interval with the stated confidence level. A
confidence is an interval within which the population parameter
is expected to lie with a certain confidence level. To increase
the probability of getting accurate estimates, the sample should
be a true representation of the population. This means that
population individuals are well represented in the sample. This
can be done through the simple random sampling for selecting
the sample for the study. Random sampling ensures that each
subject in the population has an equal chance of being selected.
When sampling for the customers to be included in the
qualitative survey, customers should be selected at random. The
size of the sample should be large enough, depending on the
size of the population (Sahu, 2015).
Linear regression is a way of identifying the linear relationship
between two variables in a study. Linear regression would be
useful in the case of the American Airline Group as it would
help in the identifying the relationship between operational cost
and financial capability. Linear regression involves two
variables; the dependent variable and the independent variable.
In the case of the American Airline Group, the dependent
variable is the operational cost while the independent variable is
the financial capability of the merger company. It is expected
that as a result of merger formation, the financial capability of

4. the new company is higher than that for the individual
companies. This would also increase the operational efficiency
of the new business. Linear regression can be used in trend
analysis. Trend analysis is the analysis of the change in a data
set within different times. After collecting and analyzing data at
different times, the results are compared after which the trend
can be observed (Weisberg, 2014).
Time series is used to study the variations in data over a given
period. Time series requires that data be collected at more than
one points and the direction in which the data may be shifting
identified. This helps the company to make necessary plans
towards the success of the business. The American Airline
Group can use time series to analyze customer satisfaction from
the services offered by the new merger. This would require that
the company collects data on customer satisfaction in different
times. If the degree of satisfaction seems to be decreasing, the
company may respond through the introduction of new services.
The company can also use time series to analyze the trend in the
number of customers using its services. To respond to the new
trend, the company may initiate new advertisement plans
(Brockwell, & Davis, 2016).
ReferencesTop of Form
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5. Top of Form
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Bottom of Form
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Bernstein, S., & Bernstein, R. (2011). Elements of statistics II:
Inferential statistics. New York: McGraw Hill Professional.
Brockwell, P. J., & Davis, R. A. (2016). Introduction to time
series and forecasting. Cham: Springer.
Holcomb, Z. C. (2017). Fundamentals of descriptive statistics.
London: Routledge.
Sahu, P. K. (2015). Estimation and inferential statistics. Place
of publication not identified: Springer.
Weisberg, S. (2014). Applied linear regression.
Business Decision Making Part One
QNT275

6. US Airways and American Airlines merger
The US Airways and the American Airlines merged in 2013 to
form the American Airlines Group which serves 336
destinations across the world. This merger presents an
opportunity to the airline group due to increased outreach
globally. The newly created airline's group serves both business
and pleasure travels with the corporate customers are expected
to be the biggest customer group. The airline's group expected
to have an increase in its revenue as it expands its customer
base both locally and internationally. The merger presents a
strengthened position of the airline group in the market and an
upper hand in competing against airlines (Reed & Reed, 2014).
Will the merger create an opportunity to generate increased
financial and operational synergies? The cost-saving aspect
that the merger presents by reducing flights that fly the same
routes and also reduce flights on the international destinations
that were served by both airlines previously. The merger uses
low cost, fuel efficient aircraft and increased sitting capacity of
more than 50 per aircraft subsequently reducing operational cost
(Reed & Reed, 2014). Previous mergers in the industry have
witnessed increased cost synergies and the similar result was
expected in the merger between the two airlines. Some of the
airlines that have benefited from mergers include the Delta
Airlines with the Northwest Airlines merger in 2008 that
experienced higher cost synergies of more than $1 billion.
The merger brings cost-saving practices by increasing the use of
fuel efficient aircraft which is expected to be a long-term
achievement for the American airline group. The airline plans to
replace the 56-seat aircraft with 76-seat aircraft which are more
fuel efficient. This move reduces expenses that individual
companies would have spent in repairing the old aircraft.
Aircraft with larger capacities are economical as flight numbers
are reduced between destinations.

7. Operational and the financial costs are the variables in the
decision to create a merger between the two airline companies.
Operational costs is a dependent variable and are influenced by
the financial capability of the company. The two airlines
cannot achieve the expected success that the merger would
achieve within a span of three years because the cost of
operations is high. The merger presents an opportunity the
airlines to expand and grow its operations globally through
already established links. The change in operational cost can be
measured by determining the operational changes influenced by
increased financial capability of the merger compared to the
individual airline's operations.
The financial capability is an independent variable that affects
the operational costs of the airline. It is evident that the
financial capability of the individual airlines limits the
operational costs. The merger increases the financial capability
of the company through the contribution from two companies.
This aspect of the merger affects the possible expansion and
success of the airline created. In research, it is variable that can
be manipulated to create a result that is desirable. It is evident
that the operational cost relies on the airline's financial
capability of the company, therefore, the merger is bringing
pool of resources that the created airline would use to expand
its operations.
The research area is likely to have both quantitative and
qualitative data, therefore, a mix of research methods can be
employed to conduct the research. The American Airlines Group
operational cost evidence can be collected through quantitative
data collection methods that include quantitative observations
and quantitative surveys. Quantitative observation can be done
by counting the number of passengers that could access the
services given by the airlines. The merger plans to increased
aircraft capacity is a change that can be quantified through
passenger data stored in the newly created airline's database.
The change is expected to increase the operational cost of the
airlines which can be measured and the opportunity created by

8. the merger can be identified.
Quantitative surveys can be administered to the customers of
the airlines to determine the impact of the change brought by
the merger. These surveys provide closed questions to the
respondents and they can only choose from the options given.
These surveys can be administered asking the change in the
financial expenditure of the customers and how much the
merger has impacted their choice of airlines. This form of data
collection allows the researcher to create generalizations and
provide a scope to the impact of the merger.
The financial capability of the airline increased compared to the
individual airlines whose budget was limited due to few
destinations plied. From projections made by the merger
company and business experts, it is evident that there would be
an increase in the earnings and growth. The merger increases its
presence in the airline industry consequently reducing
completion from fierce rivals including the Delta Airlines.
Evidence of increased financial capability can be identified
through quantitative data collection method such company
survey audits. This would be used to establish the expenditure
of individual companies and the change in the expenditure of
the merger airline. The financial capability of the merger airline
is higher as the operational costs is expected to rise due to
increase in the scope of operations. The merger presents a wider
market that the airline has to retain and increase its presence.
The pool of resources brought by the two companies provides an
opportunity for the merger to expand its market reach.
The use of the qualitative data collection method identified
provide valid data because they provide the expected data.
Quantitative data from the airlines can be collected using a
qualitative method such as a survey of audits from the company.
It provides specific information that the researcher requires to
establish a change experienced by the airline. The research
method provides the reality of the changes the airline has
experienced. The methods used can be used to administer
research on other airlines which have gone through the

9. experience and the chances pf replicating the findings is high.
The method of collection is suitable for research on airline
industry as they have a greater chance of providing actual
information. For example, the use of quantitative observation is
suitable for the study as it requires a researcher to search
number of passengers that have used the airline since the
merger and compare to the number of passengers that previously
used the individual airline (Carmines & Zeller, 1979).
References
Carmines, E. G. & Zeller, R. A. (1979). Quantitative
Applications in the Social Sciences: Reliability and validity
assessment : SAGE Publications Ltd doi:
10.4135/9781412985642
Reed, T., & Reed, D. (2014). American airlines, us airways and
the creation of the world's largest airline. Retrieved from
http://ebookcentral.proquest.com
Purpose of Assignment
This assignment provides students with practice in
understanding when or why ANOVA and linear regression are
identified based on parameters. Students will learn to implement
these statistical measures for better business decision-making.
Assignment Steps

10. Prepare an 11 slide Microsoft® PowerPoint® presentation for
the senior management team based on the business problem or
opportunity you described in Weeks 3-4. WEEK'S 3 AND 4
ASSIGNMENTS ARE ATTACHED.
Include on the slides what you would want the audience to see
(include appropriate visual aids/layout) and include in the
speaker's notes section what you would say as you present each
slide. If any source material is quoted or paraphrased in the
presentation, use APA citations and references.
Draw on material you developed in the Week's 3 and 4
assignments
Include the following in your presentation:
1. Introduction slide
2. Agenda slide
3. Describe the organization, with a brief description
4. Explain the business problem or opportunity and describe the
hypothesis
5. Analyze why the business problem is important
6. Identify what variable would be best to measure for this
problem and explain why. Also identify statistical methods used
to analyze data
7. Apply data analysis techniques to this problem (tell which
techniques should be used: descriptive statistics, inferential
stats, probability) and explain why
8. Apply a possible solution to the problem/opportunity, with
rationale
9. Evaluate how data could be used to measure the
implementation of such a solution
10. Conclusion
11. Reference slide (if any source material is quoted or
paraphrased throughout the presentation)
Format your assignment consistent with APA guidelines.