Business Intelligence – Data Analysis of US Data Source From the list of large datasets select a data containing data on United States subjects. You are to define a business problem this dataset can a

Business Intelligence – Data Analysis of US Data Source From the list of large datasets select a data containing data on United States subjects. You are to define a business problem this dataset can a
MIS540 Portfolio Project Option #1: Business Intelligence – Data Analysis of US Data Source From the list of large datasets select a data containing data on United States subjects. You are to define a business problem this dataset can attempt to answer. You are required to create business questions and hypotheses to further define the scope of your analyses. You are to create a SAS dataset containing only the variables needed for your analyses thus filtering out any unnecessary data from your analysis work.  Your analysis should include the necessary descriptive analytics tests to communicate your understanding of what story the data is telling us. Also, your analysis should include the necessary predictive analytics tests to assist decision makers in achieving their business goal of future business growth. Your deliverables for this Portfolio Project are: Business questions Hypotheses Descriptive statistics to include charts, graphs, tables, business insights, and the story the data is telling us Predictive statistics to include charts, graphs, tables, business insights, and the story the data is telling us Analysis of findings with respect to business questions and hypotheses Recommendations for further analysis: what other data sources, including big data sources, could the organization utilize to help them achieve their business goals. Limit the charts, graphs, and tables in your analysis report to only those figures needed to support your findings and analysis. Do not include statistics outputs that are not relevant to your analysis. Your analysis report should be comprehensive yet concise, specific, and most importantly, insightful. In previous Portfolio Milestone assignments, you submitted business questions, hypotheses, and a preliminary list of descriptive and predictive statistics tests. You are expected to incorporate your instructor’s feedback into this final submission. Your paper should be 8-10 pages in length, not counting the title page and references page, and must refer to three scholarly sources, as well as the course materials. It should be well written and conform to the guidelines of APA.
Business Intelligence – Data Analysis of US Data Source From the list of large datasets select a data containing data on United States subjects. You are to define a business problem this dataset can a
10 United States Data United States Data Business problem. A clothing company is planning to establish itself in Boston City. However, to take advantage of the Boston clothing market, the company must ensure that its business products and services align well with the population’s needs. Targeting the right customers is one of the key things that will ensure success. Boston has a diverse population in terms of age, gender, level of educational attainment, household/individual income, among other distinguishing factors. As an investment analyst for the company, I am tasked with researching and analyzing the key factors that must be evaluated before investing in Boston city. Business Questions. The primary business question is whether it is more feasible for the company to target more male customers than female customers or vice versa. Refining a large market into small market segments is key to ensuring that the company adjusts its marketing and promotion strategies in a way that best attracts its target customers. According to the world population review, the population of Boston in 2021 was 696, 295. Of these, 362, 142 are female, while 332, 153 are male (World Population Review, 2022). Despite this being the case, the organization must feasibly assess and evaluate the population to determine which gender makes the perfect business customer. This will be done by comparing income levels for both genders. The null hypothesis states that there will be no notable income differences between the male and female gender. The alternative hypothesis states that there will be significant income differences between the male and female genders residing in Boston city. A total of 128 employed participants between the age of 25-65 were randomly selected to participate in the evaluation. Out of these numbers, 64 were males, and 64 were females. The company will evaluate the potential of each gender being the primary target customer group by studying the distribution of income among study participants. Specifically, the mean, median, and overall income distribution metrics will be assessed. Fig 1: SAS Program for arriving at the mean salary and standard deviation among males. Fig 2: Results for the mean salary and standard deviation among males. Fig 3: SAS Program for getting the median salary among males. Fig 4: Result for the median salary for males. Fig 5: SAS Program for arriving to the mean salary and standard deviation among females. Fig 6: Results for the mean salary and standard deviation among females. Fig 7: SAS program for arriving at the median salary among females. Fig 8: Results for the Median Salary among females. From evaluation, the average salary among males is $53, 767 while the average salary among females is $47, 777. The median salary among males is $49, 851 while the median salary among females is $44, 823. Fig 9: SAS program for the graphical representation of salary distribution among males. Fig 10: Result shows a graphical salary distribution among the male population. Fig 11: Results showing a graphical representation of salary among females. According to the graphical presentation of income among the male and female gender, it is evident that income is unequally distributed among males and females. A significant difference in income distribution is evident. Therefore, the alternative hypothesis states that there will be significant income differences between the male and female genders residing in Boston city is true. Based on the analysis of mean, median, and overall income distribution among the male and female gender, the company should focus on the male market since it has a higher purchasing power than the female gender. Therefore, business strategies, including marketing and promotion strategies, should be formulated to attract the male gender to the business. Further data analysis should make use of big data categories such as the behavioral and attitudinal categories, which align well with a company’s marketing needs. Reference World Population Review (2022). Boston, Massachusetts Population 2022. Retrieved February 5, 2022, from https://worldpopulationreview.com/us-cities/boston-ma-population.
Business Intelligence – Data Analysis of US Data Source From the list of large datasets select a data containing data on United States subjects. You are to define a business problem this dataset can a
1 United States Data United States Data Business Problem A clothing company in the United States plans to establish its business in Boston City. Successful organizations ensure that they provide products that satisfy the needs and preferences of their target market. Boston comprises different demographic groups based on age, level of education, gender, sexual orientation, occupation, individual/household income, among other distinguishing factors. Therefore, for the clothing company to achieve success when it establishes its business in this city, it needs to make sure that it offers business products and services that align with the needs of different demographic groups. Being the investment analyst for the clothing company, I was tasked with studying and examining the differences in income in four demographic groups, including gender, age, race, and households, to provide the information which the organization would assess before investing in Boston city. Variables in the SAS dataset The two main variables from the company’s dataset were males and females. The clothing company analyzed whether income differs significantly between these two groups. The sample comprised 128 respondents aged 25 to 65 with an equal distribution between the two variables, i.e., 64 were males, and 64 were females. Business Questions The following four business questions were utilized to analyze the clothing company’s demographic factors before establishing its business in Boston. Should the clothing company target more male or female customers? Should the clothing company target the young population more than the elderly? Should the clothing company target all races or a specific race? Should the clothing company target more family households than non-family households? Each question is crucial in the analysis used to address the above business problem. For instance, the first business question will examine the relationship between gender and income to determine which gender earns the most income. This information will help the clothing company determine the gender category they should target more with their products. In the same context, the second question will study the income of different age groups to provide more products to meet the needs of the age group with the highest income. Similarly, the third question will identify which racial group earns the most income. Lastly, the fourth question will check if the income in family households is different from non-family households to determine which group the business should focus on. These results will help the clothing company customize its products to satisfy the demographic group’s needs and preferences that earn the most income. Hypothesis Business Question 1: Should the clothing company target more male or female customers? Null Hypothesis: There will be no significant income differences between the male and female genders residing in Boston. Alternative Hypothesis: There will be significant income differences between the males and females residing in Boston. Business Question 2: Should the clothing company target the young population more than the elderly? Null Hypothesis: There will be no significant income differences between the young and elderly populations residing in Boston. Alternative Hypothesis: There will be significant income differences between the young and elderly populations residing in Boston. Business Question 3: Should the clothing company target all races or a specific race? Null Hypothesis: There will be no significant income differences between racial groups in Boston. Alternative Hypothesis: There will be significant income differences between racial groups in Boston. Business Question 4: Should the clothing company target more family households than non-family households? Null Hypothesis: There will be no significant income differences between family households and non-family households. Alternative Hypothesis: There will be significant income differences between family households and non-family households. Statistical Tests The statistical tests used to analyze the business problem include the median, Chi-square, and t-test. Business Question 1: Should the clothing company target more male or female customers? The statistical test that will be used to answer this business question and either prove or disapprove of the hypothesis is a median test. This statistical test is often utilized in comparing the medians of two different groups to establish whether they differ (Stephenson, 2016). Therefore, the median test is the definitive test for this business question because it will compare the medians of the income between male and female customers to establish if they differ significantly. Business Question 2: Should the clothing company target the young population more than the elderly? The statistical test that will be used to answer this business question and either prove or disapprove the hypothesis is the Chi-square test. This statistical test analyzes differences in independent variables (Hayes, 2021). Therefore, this test is appropriate for this business question because the chi-square statistic obtained from the test will tell how much difference in income exists between the young population and the elderly Business Question 3: Should the clothing company target all races or a specific race? The statistical test used to answer this business question and either prove or disapprove of the hypothesis is the t-test. Hayes (2021) highlighted that t-tests are used to assess whether there is a notable difference in means between two different groups that might be correlated. Similarly, this test will establish whether there is a significant income difference between racial groups in Boston city. Business Question 4: Should the clothing company target more family households than non-family households? The statistical test that will be used to answer this business question and either prove or disapprove of the hypothesis is the Median test. This test will compare the medians of the income between family households and non-family households to assess whether they differ significantly. Visualizations The visualizations that I intend to use are graphs, tables, charts, scatter plots. Graphical visualizations will enable quick analysis of the results at one glance, thus helping the clothing company make informed decisions about establishing their business successfully in Boston. Secondly, tables will summarize the mean income of each category in the four different demographic groups. Similarly, charts and scatter plots will highlight the information recorded on the tables to allow a more straightforward interpretation of data. Concerns The main concern in completing this portfolio project is the possibility of statistical errors since the sample used in the analysis was smaller. In hypothesis testing, statistical errors such as type I and type II errors are inevitable. These errors might arise due to errors of omission and errors of commission. For instance, if the results obtained from one of the statistical tests indicate that we reject the null hypothesis when it needs to be accepted, this will lead to a Type I error. If the results indicate that we accept the null hypothesis when it should be rejected, this will lead to a Type II error (Bhandari, 2021). Therefore, to minimize such errors, the sample size used in the test should be larger. References Bhandari, P. (2021). Type I & Type II Errors | Differences, Examples, Visualizations. https://www.scribbr.com/statistics/type-i-and-type-ii-errors/ Hayes, A. (2021). Chi-Square (χ2) Statistic. https://www.investopedia.com/terms/c/chi-square-statistic.asp Hayes, A. (2021). T-Test. https://www.investopedia.com/terms/t/t-test.asp Stephenson, G. (2016). Mood’s Median Test: Definition, Run the Test, and Interpret Results. https://www.statisticshowto.com/moods-median-test/