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MBA 504 Project Guidelines and Rubric
Competencies
In this project, you will dem
MBA 504 Project Guidelines and Rubric
Competencies
In this project, you will demonstrate your mastery of the following competencies:
MBA-50716: Use descriptive statistics for business analysis
MBA-50679: Perform regression analysis to address an authentic problem
MBA-50880: Apply statistics in the business environment
Overview
You have been hired as a consultant by TC Ice Cream. As part of its expansion plan, TC Ice Cream wants to limit the number of flavors that they sell and only focus on those that are the most profitable. You will do an analysis of two flavors for a specific division and determine which flavor should be kept and which should be removed.
Option A: Keep Flavor One
Option B: Keep Flavor Two
The TC Ice Cream management team has tasked you with doing an in-depth analysis to determine which of the two options will be the most profitable, given the monthly advertising expense range of $500–$2,750. Use the division that you selected in Module Two and the two flavors that you selected for Milestone One. Consider the TC Ice Cream data set that contains data about quantity sold, advertising expenses, flavor rating, social media posts, and event promotions.
Prompt
Part 1: Data Analysis Workbook
Analyze the data from the provided TC Ice Cream data set and identify current and future trends and patterns in operations.
Complete the following visualizations for each flavor. The visualizations for Flavor One should be completed in the “Flavor One Analysis” sheet and the visualizations for Flavor Two should be completed in the “Flavor Two Analysis” sheet of the TC Ice Cream Excel Workbook. It is recommended that you use pivot table filtering to filter the data to the specific division and flavor you have selected.
Specifically, you must address the following rubric criteria:
Present the key descriptive statistics for the five quantitative variables in a table (quantity sold, advertising expenses, flavor rating, social media posts, and event promotions). The key descriptive statistics include the mean, median, standard deviation, and range.
Analyze the TC Ice Cream data to identify trends and patterns for the two flavors you have selected. For each flavor, create the following visualizations:Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Quantity Sold to provide a visualization displaying quantity sold by month.
Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Flavor Rating (average) to provide a visualization displaying flavor rating (average) by year/quarter/month.
Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables Quantity Sold (clustered column) and Advertising Expenditures (line – secondary axis).
Create a combo chart using the qualitative variable Date (x-axis) and the quantitative variables Quantity Sold (clustered column) and total – Social Medial Posts and Event Promotions (line – secondary axis). Hint: create a pivot table variable to sum the social media posts and event promotions.
Create a box and whiskers chart using the qualitative variable Quantity Sold. This will help identify any outliers in the Quantity Sold data.
Create a histogram for the qualitative variable Flavor Rating. It is recommended to use the data analysis “add-in” and the analysis tool “Histogram” to create the data for the visualization.
Outliers: Identify any outliers that you see and explain how they have an impact on the overall admission and expense trends. Outliers are the data points that can have an impact on your averages and basic descriptive analysis.
Perform two bivariate regressions to provide recommendations.
For the first bivariate regression for Flavor One, the dependent variable should be Quantity Sold. Choose an independent variable from one of the remaining attributes (Advertising Expenses, Flavor Rating, Social Media Posts, Event Promotions).
Use the Flavor One Bivariate Analysis sheet.
For the second bivariate regression for Flavor Two, the variable should be Quantity Sold. Choose an independent variable from one of the remaining variables (Advertising Expenses, Flavor Rating, Social Media Posts, Event Promotions).
Which independent variable seems most appropriate to lead you to a monthly quantity sold of 3,000–12,000 gallons?
Perform two multivariate regressions to provide recommendations. For the first multivariate regression, the dependent variable should be Quantity Sold (the column in the data set). Choose two independent variables from one of the remaining attributes (Advertising Expenses, Flavor Rating, Social Media Posts, Event Promotions). Use the Flavor One Multi. Analysis sheet.
Which combination of the attributes seems most appropriate to lead you to the expense range of $500–$2,750?
For the second multivariate regression, the dependent variable should be Quantity Sold (the column name in the data set). You should choose two independent variables from one of the remaining attributes (Advertising Expenses, Flavor Rating, Social Media Posts, Event Promotions). Use the Flavor Two Multi. Analysis sheet.
Which combination of the attributes would seem appropriate to lead you to a monthly quantity sold of 3,000–12,000 gallons?
Part 2: Final Recommendation Analysis PowerPoint Presentation
Create a PowerPoint presentation designed for the TC Ice Cream management team to share the results of your analysis and provide your final recommendation.
Current State Analysis (slides 1–3): State the option (A or B) that you chose and three reasons for your choice.Which option (Option A or Option B) would you choose based on your analysis, given the monthly expense range of $500–$2,750?
Why did you choose your selected attributes?
Describe any relationships or trends you observed while conducting your analysis.
Predictions and Trends Analysis (slides 4–6): Present the predictions based on the regressions that you have analyzed.Briefly describe the key elements for each regression presented in Excel. Cite the regression coefficient, regression line equation, p value, and significance F in your description.
Which of the independent variables are impactful, and why?
Executive Audience Summary (slide 7): Summarize your findings for an executive audience.
What to Submit
To complete this project, you must submit the following:
TC Ice Cream Excel Workbook:
Submit your completed TC Ice Cream Excel Workbook as an Excel file.
Final Recommendations Analysis Presentation:
Submit a PowerPoint presentation with 7 to 10 slides. There is no template for this assignment, so you may use an earlier presentation template or create your own design. Any sources should be cited according to APA style. Consult the Shapiro Library APA Style Guide for more information on citations.
Project Rubric
CriteriaExemplary (100%)Proficient (90%)Needs Improvement (70%)Not Evident (0%)Value
Descriptive StatisticsExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerPresents descriptive statistics for the five quantitative variables (mean, median, standard deviation, and range) with no errors or omissions for the two flavors selectedShows progress toward proficiency, but with errors or omissions; areas for improvement may include presenting error-free statistics or including critical dataDoes not attempt criterion10
Flavor One Trends and ChartsExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerCreates six visualizations for flavor one to identify trendsShows progress toward proficiency, but with errors or omissions; areas for improvement may include creating more charts or trends, and using data variables with minimal errors or omissionsDoes not attempt criterion10
Flavor Two Trends and ChartsExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerCreates six visualizations for flavor two to identify trendsShows progress toward proficiency, but with errors or omissions; areas for improvement may include creating more charts or trends, and using data variables with minimal errors or omissionsDoes not attempt criterion10
OutliersExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerIdentifies specific outliers in the data and describes how specific outliers impact the descriptive analysisShows progress toward proficiency, but with errors or omissions; areas for improvement may include highlighting specific outliers and their impact on charts or trendsDoes not attempt criterion10
Bivariate RegressionsExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerPerforms two linear bivariate regressions to provide recommendationsShows progress toward proficiency, but with errors or omissions; areas for improvement may include clearly citing each of the outputs from regressions used to weigh the model’s usability, citing the regression best fit line model, and analyzing the scatterplot, best fit line, and residual plotsDoes not attempt criterion10
Multivariate RegressionsExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerPerforms two linear multivariate regressions to provide recommendationsShows progress toward proficiency, but with errors or omissions; areas for improvement may include clearly citing each of the outputs from regressions used to weigh the model’s usability, citing the regression best fit line model, and analyzing the scatterplot, best fit line, and residual plotsDoes not attempt criterion10
Current State AnalysisExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerExplains the analysis in a clear and detailed mannerShows progress toward proficiency, but with errors or omissions; areas for improvement may include ensuring the analysis includes specific mention of data points, outliers, and trends that connect strongly with Excel analysisDoes not attempt criterion10
Predictions and Trends Analysis: Bivariate RegressionExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerDescribes the key elements for each bivariate regression analysis in a clear and detailed mannerShows progress toward proficiency, but with errors or omissions; areas for improvement may include ensuring that the report clearly mentions the attributes used for bivariate regression, connects with the given scenario, or cites the usability of the bivariate regression model to predict outcomes; connects the analysis strongly with Excel analysisDoes not attempt criterion10
Predictions and Trends Analysis: Multivariate RegressionExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerDescribes the key elements for each multivariate regression analysis in a clear and detailed mannerShows progress toward proficiency, but with errors or omissions; areas for improvement may include ensuring that the report clearly mentions the attributes used for multivariate regression, connecting with the given scenario, and citing the usability of the multivariate regression model to predict outcomes; connects the analysis strongly with Excel analysisDoes not attempt criterion10
Executive Audience SummaryExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerCreates a summary of findings that is appropriately tailored for an executive audienceShows progress toward proficiency, but with errors or omissions; areas for improvement may include relying too heavily on visual or written analysisDoes not attempt criterion5
Articulation of ResponseExceeds proficiency in an exceptionally clear, insightful, sophisticated, or creative mannerClearly conveys meaning with correct grammar, sentence structure, and spelling, demonstrating an understanding of audience and purposeShows progress toward proficiency, but with errors in grammar, sentence structure, and spelling, negatively impacting readabilityDoes not attempt criterion5
Total:100%
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