**Use attached word document and add to it. Some work has been done in the previous unit.** Prepare an analytics report of 8–10 pages. Your analytics report should contain the following: Section I Business Question (or other appropriate heading) Analyze the business question or problem.
Explain the business problem your analysis is attempting to address and how it will do so. Section II Data Analysis Techniques and Methods Summarize the methods you have selected to analyze the data.
Be sure to support your selections with examples from previous
applications (experience) and your research. You must justify all of
your techniques, including the descriptive and inferential techniques,
but justifying and supporting descriptive techniques may be as simple as
explaining why it is the most appropriate graph, chart, or summary
method for your data. Section III Descriptive Statistical Analysis Using the data set you downloaded in Assessment 2, create 5 descriptive statistical techniques.
These may be graphs, charts, or numeric summaries but must be
appropriate for the type of data and must assist in addressing the
business question or problem.Copy/paste the graphs, charts, or summaries from Excel into your document.Remember that there are different options based on the data type
(qualitative versus quantitative data) and that other considerations
must be taken when choosing the appropriate descriptive techniques for a
particular type of data. Section IV Inferential Statistical Analysis Use the data set you downloaded to complete one inferential
statistical technique to estimate, test, or predict something using the
inferential statistical methods you learned in this course.
The method you choose should be based on your work in Assessment 2.Support your choice of method using prior analytic project experience and/or your own research.Within this section include:
Assumptions: All assumptions required to use
the technique you selected should be checked and explained (when there
is no way to validate or check that the assumption is met). Any
assumptions that may not be met should be included in your cautions and
limitations of your analysis.Results: Guidance on when, where, and with
whom the results of your analysis should be used should be included in
your generalizations section and should be based on the source of the
data, data collection methods (if any are provided with your business
scenario), and potential issues with how and when the data was
collected, recorded, and so on.Conclusions: Your conclusion should restate
the business question or problem, identify the methods used (both
descriptive and inferential methods), and summarize the results and
findings (in business language).Cautions, Limitations: Your cautions and
limitations should include any potential issues or limitations in using
your analysis due to the assumptions not being met or being minimally
met.Generalizations: Your generalizations should
include notes about when and how the results of your analysis should and
should not be used, specifically focusing on the contents of the data
set you have analyzed. Deliverable Format The analytics report is a professional document and should therefore
follow the corresponding MBA Academic and Professional Document
Guidelines, using double-spaced paragraphs. Write for management or
other analysts. You must also include: 8–10 pages in length, not including the title page, references page, or abstract.Title page.Abstract (optional).References page.At least 3 supporting resources.APA-formatted references.Appendices for graphs, charts, and summaries if you prefer, rather than including them in the text of your report. Evaluation By successfully completing this assessment, you will demonstrate
your proficiency in the following course competencies through
corresponding scoring guide criteria: Competency 1: Explain how data management techniques and tools are used to support business decisions.
Analyze the business question.Explain the results of the analysis and how the analysis addresses the business question. Competency 2: Use analytic and statistical techniques to make meaning of large quantities of data.
Summarize the descriptive and inferential statistical techniques used.Create descriptive statistical techniques appropriate for the type of data used. Competency 3: Apply data analytic techniques to make inference about a business need.
Complete inferential statistical techniques that are appropriate for the data used and address the business question.Explain any assumptions, cautions, limitations, and generalizations. Competency 4: Present the results of data analysis in clear and meaningful ways to multiple stakeholders.
Correctly format citations and references using current APA style.Write content clearly and logically with correct use of grammar, punctuation, and mechanics.

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Population Analytics
Population Analytics
This paper focuses on the analysis of the population characteristics that will bind the
demographic engagement as well as economic development of the state of Texas. The study of
the comparison and contrasting of this development is measured with the development and
growth of New York State. Therefore, New York is used as a test statistic in this business
project plan. In line with this argument, real estate business is the best business condition that
can be used to configure the issue considerations of a successful business session. Ensuring a
successful marketing and pricing strategy can be difficult. In real estate business, spatial
analysis of the location, and economic status this will enhance the development proper analysis
procedure for improved marketing. Common demographic characteristics that are considered
include Literacy rate, Economic Status, Illiteracy rate, dependency ratio, Gross Domestic
Product and sex ratio analysis for both Texas and New York.
Keywords: [Sex ratio, Literacy rate, economic status, dependency ratio, GDP]
Population Analytics
Real Estate Business in Texas
The most critical consideration in the development of Real Estate business analysis is
the population characteristics (Noe et al., 2016). To be able to solve the issue of housing and
mortgage development in economic growth, there are different factors to consider. It includes
the financial status of the population in the business location area. It is developed based on the
demographic statistic that is obtained from the US Department of Economic Research. The
combination of the different kinds of houses in Texas and the New York help in determining
the average pricing mode depending on the economic level and status of the respective resident
Business Problem
The agility behinds determine the success of any business it’s strategic management. It
is difficult most of the time to deal with companies that have a static target audience. In this
case, real estate business is the best business condition that can be used to configure the issue
considerations of a successful business session. Ensuring a successful marketing and pricing
strategy can be difficult. In real estate business, spatial analysis of the location, and economic
status this will enhance the development proper analysis procedure for improved marketing. In
this case, there is a consideration of real estate pricing model in Texas and New York (Neiger
et al., 2016). It will enhance a proper house pricing criteria and best market pricing strategy for
real estate businesses. To be able to come with this analysis, two randomly selected houses in
Texas and New York are analyzed and their prices determined. It involves the price of house
Population Analytics
Data to be Used
The data that is best to use for real estate marketing and pricing analysis is obtained
from the population information and demography of Texas and New York. The spatial
differentiation as well as economic and population diversity are contributing factors to the
choice of these States for comparison and analysis.
Analytic Inferential Method
Over the last two years, Texas has experienced a population growth rate of 1.45% most
of which is contributed to by permanent resident migration. It has resulted in a subsequent
increase in demand for residential houses most of which are homes for nuclear family size. The
nuclear families have a demographic description of average children per family of 1.7. It means
that in every family, there are about two children. It makes the demand for residential houses
to range between 2 bedroomed or more. It creates a perfect choice for Jane to have her property
choice to have a minimum of 2-bedrooms.
The Texas population has a median age of 53. It means that most of the people in this
region are active in the job market and are earning a living. There median weekly income is at
$1005 (Clough et al., 2014). The median weekly rent paid in this region is $345. And the
average motor vehicle per dwelling is 2.1. It means that there will be a demand for packing
space for 2 in every property. Jane has to make this consideration. Besides, most private
properties are built in up-countries whereas rented and public parks are high in cities.
Inferential Statistical Technique
Some of the official statistics of the Texan population, as well as the New York
population, include sex ratio, dependency ratio, child-woman ratio, economic status, and
Population Analytics
literacy level. All these factors contribute significantly to the development of common interest
of ability and ease of business investment and the creation of employment (Coon, 2015).
Inferential Statistical Technique Justification
The first property is a house in Dallas, Texas. It is a four-bedroomed house, and that is
located in the up-country area with a large neighborhood. The home has distinct sections of
basic house requirements such as the living room, the dining room, and spacious open space at
the door entry. This house goes for $607,600. Below is a picture of the house:
The second house to be considered is one in the city of New York. It is among a set of
apartments within the periphery of the City. It is exceedingly accessible, and one could enjoy
a calm natural environment. The house has a shared pool behind the apartments. It is a threebedroomed house with spacious rooms and windows (Hambrick et al., 2016). This property
goes for $497,900. Below is a picture of the property:
Population Analytics
The key objectives of this research are:
To ascertain whether Texas is experiencing stable market prices.
To find out whether Texas’s economy experiences a steady and sustainable
economic growth.
To determine whether Texas’s population has either a high or low rate of
To find out whether Texas has achieved a balanced payment distributed across
These objectives are aimed at the development consideration for which is based upon
access to house acquisition (Coon, 2015). Factors that are most appropriate are developed on
the basis that planning and marketing are best suited for are real estate. Population
characteristics are the most statistical considerations for the marketing and pricing of houses.
Therefore the data that will be looked include economic status.
Population Analytics
Clough, R. H., Sears, G. A., & Sears, S. K. (2014): Construction project management. John
Wiley & Sons.
Coon, M. (2015): Social media marketing: successful case studies of businesses using
Facebook and Youtube with an in-depth look into the business use of Twitter.
Unpublished manuscript MA thesis, Stanford University.
Hambrick, M. E., Simmons, J. M., Greenhalgh, G. P., & Greenwell, T. C. (2016):
Understanding professional athletes’ use of Twitter: A content analysis of athlete
tweets. International Journal of Sports Communication, 3(4), 454-471.
Neiger, B. L., Thackeray, R., Burton, S. H., Thackeray, C. R., & Reese, J. H. (2014): Use of
Twitter among local health departments: an analysis of information sharing,
engagement, and action. Journal of medical Internet research, 15(8), e177.
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2016): Human resource
management: Gaining a competitive advantage.

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