Unit 1 Big D Incorporated Multivariate Techniques Analysis Paper Using the information from Units 1, 2, & 3, Big D Incorporated will be examining how multi

Unit 1 Big D Incorporated Multivariate Techniques Analysis Paper Using the information from Units 1, 2, & 3, Big D Incorporated will be examining how multivariate techniques can serve the organization best and how they can be applied to their new client, the outdoor sporting goods customer. The Board of Directors has asked you to research and explain 3 major ways in which multivariate statistics are utilized in this scenario. In this case, be sure to justify your decision.

Research using the library and the Internet to find an 1 example of how a real company has used each of the following multivariate techniques: factor analysis, multidimensional scaling, and cluster analysis. This can be considered a benchmark if you can justify how it could benefit Big D Incorporated.

Write a summary to upper management explaining the following:

How can each multivariate technique be utilized in Big D Incorporated, and what purpose would each serve?
Which technique is your preferred method, and how is your chosen multivariate technique different from the other two techniques?
What will the Board of Directors learn from your selected technique and more importantly, how will it contribute to the overall decision-making process? Ensure that your explanation is clear and concise in its explanation.

Please add your file.

For assistance with your assignment, please use your text, Web resources, and all course materials. Big D Corporation Recommendation
for
Business Expansion
Presented By
Marion Stephens
Colorado Technical University
Introduction
o Business expansion
? It is a strategy used by companies that involve increasing the number of stores where
consumers could procure items or services offered by a company.
o The process involves analyzing data to examine the suitability of a market in terms of
number of consumers
? Household income
? Employment rate
National and Territory Data
o The table indicates some of the areas that depict differences between the territory (60614)
information compared to the national data.
Occupation Summary
o Remark
? Majority of territory 60614 is in
labor force and employed
compared to the national
population.
? None of the residents worked in
Armed forces
Income Summary
o Remark
? Overall, territory 60614 has
a higher household income
compared to national figures
on average, median and per
capita
Key Takeaways from the Graphs
o From the graphs, Territory 60614 population has a higher household income compared with the
national incomes levels in terms of
? Average household income (US$ 114,615)
? Median Household income (US$69,311)
? Per Capita Household Income (US$64,426)
o Territory 60614 majority population is
? In labor force (81.10%) and 95.60 % are employed
? None of the residents in the territory works in the Armed Forces (0.00%)
Recommendation and Justification
o Compared with the national data, Big D Corporation is recommended to expand its
business to territory 60614. This is because
? The majority of the territory population are in the labor force and actually employed
? The population indicated high household income on average compared to the national
figure
o This means that the population has enough money for their sustainability as well as
spending on other things.
References
o Katal, A., Wazid, M., & Goudar, R. H. (2013, August). Big data: issues, challenges, tools and
good practices. In 2013 Sixth international conference on contemporary computing (IC3) (pp.
404-409). IEEE.
o Piekkari, R., Welch, D., & Welch, L. S. (2014). Language in international business: The
multilingual reality of global business expansion. Edward Elgar Publishing.
BIG D EXPANSION DECISION
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Big D: Expansion Decision Making
Marion Stephens
Colorado Techincal University
BIG D EXPANSION DECISION
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Big D: Expansion Decision Making
In operating a business, decision making forms the fundamental elements towards
attaining the set goals and objectives. Birt, Chalmers, Maloney, Brooks, Oliver, and Bond (2019)
defined decision making as a continuous and necessary element of administering enterprise
activities. Decisions involve a course of action selected from several available alternatives to
accomplish organizational objectives and goals. Notably, enterprise decision-making process
involves various steps essential in ensuring that the chosen course of action impact a business
positively as well as minimize possible associated risks. The method includes collecting relevant
data, identifying alternatives, weighing the available evidence, selecting among the viable
options, and lastly the taking most suitable action. Effective business decisions making process
integrate statistical analysis aimed at proving conditional statements formulated with the
presence of minimal information and open for further investigation.
Discussion
Business Scenario
Big D, an enterprise dealing with outdoor sporting products, seek to expand the business
in a new market. The expansion is one of the strategic by Big D move, focused on increasing the
company market share and corresponding growth of the enterprise profits. However, the tactical
move will depend on the most viable option between to expand to the next market or retain the
current company position. The decision on the appropriate choice depends on various available
market metrics, essential in informing the viable decision that would align the business with its
goals and objectives. The firm intends to expand in territory 60614, for the outdoor sporting
activities. Nonetheless, the company will make decision-based on statistical evaluation that will
involve comparing the national statistic with the region 60614 data. Notably, the process will
BIG D EXPANSION DECISION
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involve examining the income, occupation, and population growth, which are three primary
factors that depict the sustainability of a business in a selected market.
Chi-distribution Tool
From a business analyst perspective, the decision will include the utilization of a ChiSquare distribution tool, which is a nonparametric test. Cronin (2016) noted that nonparametric
analysis requires data that does not require fitting a normal distribution. In most cases,
nonparametric statistics include ordinal data implying that the technique does not rely on
numbers but instead depends on ranks. In this case, the Chi-Square test will aid in evaluating
various aspects of the market essential in making supported market decisions. The analysis
findings will facilitate the decision-making process for BigD enterprise regarding the viability of
expanding to the next marketplace or retain the current position,
Hypothetical Statements
Ho: There is no significant difference in income between national and territory 60614.
H1: There is a significant difference in income between national and territory 60614.
Ho: There is no significant difference in occupation between national and territory 60614.
H1: There is a significant difference in occupation between national and territory 60614.
Ho: There is no significant difference in population growth between national and territory 60614.
H1: There is a significant difference in population growth between national and territory 60614.
Results
i.
Chi-Square Test Income
The Chi-square results from the examination of the income between the territory 60614
compared with that of national profile depicts a chi-square value = 3629.69 and a critical value
of 3.841. Besides, the p-value for the chi-square is 0.0000 less than ?=0.05. Thus, we reject the
BIG D EXPANSION DECISION
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null statement and make a deduction that there is no substantial variation in income between
national and territory 60614. Thus, we are 95% confident that the average individual income in
region 60614 differs from the national average personal income.
ii.
Chi-Square Test Occupation
On the other hand, the chi-square test result for occupation between the territory 60614
compared with that of national profile depicts a chi-square value = 0.08 and a critical value of
3.841. Besides, the p-value for the chi-square is 0.9991 greater than ?=0.05, implying that there
is no statistical significance. Thus, we accept the null statement and conclude that there is no
significant variation in occupation between national and territory 60614 at 95% confidence.
iii.
Chi-Square Test Population Growth
The chi-square outcome for the population between the territory 60614 compared with that of
national profile depicts a chi-square value = 0.02 and a critical value of 3.841. Besides, the pvalue for the chi-square is 0.9995 greater than ?=0.05. Therefore, there is no statistical
significance between population growth in region 60614 and national profile. As a result, we
accept the null statement; thus, we are 95% confident there is no meaningful difference in
population increment between federal and territory 60614.
Discussion
Income reveals the level of business activities in term of the number of sales. Population
with a high income implies that consumers can spend on other items, such as outdoor sporting
products. The chi-square outcome depicts that there is a difference between individual income
levels in the national profile compared with that of region 60614. Based on the descriptive
statistics, an individual in the area earns a higher income compared to the general population
making the region viable for BigD enterprise expansion.
BIG D EXPANSION DECISION
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On the other hand, the population occupation in the selected expansion areas is also
another area of interest worth considering in the process of making business expansion decisions.
Employment is another fundamental element that reveals if a population in selected areas are
employed and earning an income. Occupation is essential in empowering consumers towards
buying items such as outdoor sporting products. Similarly, Chi-Square test results accepted the
null statement, which implies that the population occupation does not differ between national and
territory 60614 at 95% confidence. The finding makes the region suitable for business expansion.
Moreover, population growth is another factor that shows how the number of individuals
in a selected area increases. In a business perspective, population growth depicts an increase in
potential consumers for the offered products or services by an enterprise, making population
growth a significant factor in a business decision-making process. From the analysis, we
accepted the null statement indicating that there is no substantial variation in population increase
between federal and territory 60614. As a result, this makes the region viable for business
expansion.
Recommendation
From the Chi-Square analysis, it is evident that region 60614 is viable for business
expansion. Therefore, it is recommended that BigD enterprise management expand its business
in the selected territory 60614. Notably, individuals in the region have a higher income on
average compared with personal profit at the national level, while the occupation and population
growth does not differ significantly. The findings mean that the region offers good business as
well as a high level of business sustainability.
BIG D EXPANSION DECISION
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Conclusion
Business expansion is a critical strategic move fundamental towards attaining the set
corporate goals and objectives. Besides, an enterprise expansion involves an effective decisionmaking process to enhance positive business growth as well as minimize possible associated
risks. The technique includes collecting data, identifying alternatives, weighing the available
evidence, selecting among the viable options, as well as taking the most feasible action. From
the chi-square assessment, it is recommended that Big D expand the business to region 60614 for
the selected outdoor sporting products. Indeed, effective business decisions making process
integrate statistical analysis aimed at proving conditional statements formulated with the
presence of minimal information and open for further investigation.
BIG D EXPANSION DECISION
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References
Birt, J., Chalmers, K., Maloney, S., Brooks, A., Oliver, J., & Bond, D. (2019). Accounting:
Business reporting for decision making. John Wiley & Sons.
Cronin, B. (Ed.). (2016). Handbook of research methods and applications in heterodox
economics. Edward Elgar Publishing.
Marion Stephens
Colorado Technical University
Introduction
Big data analytics
o It is a complex procedure used in evaluating large dataset with the aim to uncover
important info such as
? Hidden patterns
? Unknown associations
? Consumer preferences and
? Market trends
o Helps enterprises to make supported decisions with a capacity to drive efficient operations
essential for robust business growth.
Nominal and Ordinal Data
Nominal
Ordinal
o Qualitative
o Both qualitative and quantitative
o Utilizes categories
o Ordered
o The categories are not ordered
o Numbers are ranked
o Data are not measured
o No meaningful variation between data
entries
Sporting Goods Qualitative Attributes
o Ordinal Data
? Customer satisfaction level:- ordered as 1 to 5 for attributes end-points
? Not satisfied – Extremely satisfied
? Customer needs in order of importance :- ordered as 1 to 5 for attributes end-points
? Not important – Highly important
o Nominal data
? Type of sports activities in outdoor sporting
Interval and Ratio Data
o Has a true/ absolute zero
o Numerical
o Has no true zero
o Does not include negative entries
o Depict meaningful difference
o Allows unit conversion
o Include negative entries
o The difference between entries is not equal.
Quantitative Attributes
o In Outdoor Sporting, a market researcher would like to measure the following quantitative
attributes
? Is pricing an important attribute when you are considering to purchase a sporting gear
brand? (endpoints)
• Extremely important – Not Important
? What is the age of participants in the outdoor sporting activity?
Population and Sample
o Population
? It is a set of items with similar characteristics of interest in a research or an experiment
that comprise of potentially infinite groups, for instance, the population of spectators
attending an outdoor sporting activity.
o Sample
? It a portion of a group selected to represent a total population. For instance, a sample of
100 spectators from 1000 spectators in an outdoor sporting activity.
References
o Bell, E., Bryman, A., & Harley, B. (2018). Business research methods. Oxford university
press.
o Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach.
John Wiley & Sons.
o LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data,
analytics and the path from insights to value. MIT sloan management review, 52(2), 21-32.

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