Data-Driven Decision Making

Identify a real-world business situation and use real data to perform a data analysis leading to an actionable recommendation. You are encouraged to select an issue in your workplace or program specialty area (e.g., IT management, HC management, or MBA). Publicly available data is also an option (see Course Tips).

This business situation and data will be used to complete task 2. Do not work on task 2 until you have successfully passed task 1, indicating that the business situation and data analysis plan have been approved.

Use the “Determining the Appropriate Analytical Technique” presentation in the Attachment section below and/or speak with a course instructor to help you identify the appropriate analysis technique to analyze data for these tasks.

Approved data analysis techniques include the following:

Recommended Analysis Techniques:

• regression (linear regression, multiple regression, or logistic regression)

• time series or trend analysis

Note: you need to specify the specific type(s) of time-series analysis you plan to use or consider in Task 2 – i.e., regression, exponential smoothing, moving average, seasonality using multiple regression

• chi-square

• t-test (one sample, two independent samples, or paired)

• ANOVA

• crossover analysis

• break-even analysis

Additional Approved Analysis Techniques:

• statistical process control

• linear programming

• decision tree

• simulation

Sample Solution

ACED ESSAYS