Question

dentify and analyze a real-life, business application of statistics. The “business” can be a for-profit, non-profit, small or large entity. The following are not acceptable topics:

• An application that uses descriptive statistics (i.e., graphs, percentages, measures of central tendency or dispersion)

You do not have to collect actual data from a business or apply the statistical procedure/calculate an answer.

Write a brief summary of the business context (e.g., manufacturing, marketing, finance, etc.) including the name of the company or organization.

___________________________________________

Part B: Problem/Issue

State the business problem/issue to be addressed using statistics and why this problem/issue is important to the company/organization.

___________________________________________

Part C: Statistical Procedure

Explain the statistical procedure (NOTE: Focus on ONE statistical procedure only)

1. Independent variable:

a) What is the variable: ___________________________________________

b) How it is measured, i.e. what units or categories are used (e.g., revenue measured in “dollars”; height measured as “short, average, tall”) _______________________________

c) Level of measurement (nominal, ordinal, interval, or ratio): ________________________________________

2. Dependent variable:

a) What is the variable: ___________________________________________

b) How it is measured, i.e. what units or categories are used (e.g., revenue measured in “dollars”; height measured as “short, average, tall”) _______________________________

c) Level of measurement (nominal, ordinal, interval, or ratio): ________________________________________

3. Name of the procedure/formula (e.g., ANOVA, Chi-Square, Hypothesis Test using z formula, Regression Analysis, etc.). NOTE: The procedure/ formula must be one that was covered in the course: ___________________________________________

4. Describe the statistical rationale/justification for choosing this procedure/formula: ___________________________________________

5. Describe how the data are collected by the business/organization: ___________________________________________

6. Describe how the data are analyzed (i.e., identify the steps in the statistical procedure): ___________________________________________

Part D: Decision/Interpretation

Explain the type of business decision that the company/organization would make as a result of this statistical analysis.

Answer 1

Part A: Context(marketing):

Associated Food Holdings, LLC is the company in New York that provides services to independent grocery retail stores.

Part B: Problem/Issue:

It is required for the company to analyze the data on sales and advertisement expenditure. It's an issue for the company because it has to decide on how much amount to invest in the advertisement this year and next few years for the desired amount of sales.

Part C:

1.

a)

Independent variable(X): Advertisement expenditure

b)

It is measured in dollars.

c)

Levels of measurement: Ratio level (because it has equal intervals and true zero point).

2.

a)

Dependent variable(Y): Sales

b)

It is measured in dollars.

c)

Level of measurement: Ratio level

3.

The required procedure is: Regression Analysis

4.

This procedure is chosen because regression analysis is used to predict the amount of dependent variable (here sales) for the given amount of independent variable (here advertisement expenditure) and also to determine the amount advertisement expenditure for the desired amount of sales.

5.

The data is collected from its sales reports and various other reports that contain sales data and advertisement expenditure data for several recent years or months.

6.

First the decision of organising the data such as month wise or year wise or quarterly wise, etc. has to be made. Let's say "month wise". Now, we take recent months (say, 40 months) data on sales and advertisement expenditure. Then we run regression analysis on the data after testing if the data satisfies the assumptions of regression analysis for which we need to see if the data follows any pattern such as linear regression, curvilinear regression, logistic regression, exponential regression, etc,. in order to decide what model is suitable for the data collected.

Then we test the significance of the model such as testing for regression coefficient (or slope) to determine if the model can be used.

If the model is significant, then we find the equation (regression model) in which we substitute the amount of independent variable (X) to predict the amount of dependent variable (Y) or we substitute the desired amount of dependent variable (Y) to find the amount of independent variable (X).

Part D:

After substituting the desired amount of sales (Y) in the regression equation, the company knows what is the amount of advertisement expenditure (X) that is expected to be invested in that particular month.

Now by seeing the constraints such as the maximum amount of advertisement expenditure as per the company policy, it decides on how much to invest in advertisement and knows what the expected amount of sales is using the regression model.