Course Content

app.box.com/s/mahej76f4yoxr056kzjyy5thnwxtad0dWelcome to MKTG 325 - Introduction to Marketing Analytics - at the University of Louisiana at Lafayette. In this course, we will use Excel to clean and organize a dataset, perform descriptive statistics, and test hypotheses. Finally, we will communicate our recommendations to management. The required textbook remains Business Analytics: Communicating with Numbers by Jaggia, Kelly, Lertwachara, and Chen. We will frame our recommendations using the language associated with resource advantage theory. Of Theory, Competition, & Marketing provides a discussion of this theory.

The reflection essay, homework assignments, topics, participation discussion, and student information sheet can be accessed by clicking this link.

Datasets for use in class can be found through this link.app.box.com/s/mahej76f4yoxr056kzjyy5thnwxtad0d

The mini case assignment can be accessed by clicking on this link. 

The final case will be available about midway through the term.

If you are looking for datasets to play with, click this link. More can be found through this curated list.

The course syllabus is available by clicking this link.

Helpful Content

Additional resources devoted to:

• Excel
• designing​
• making a grade book
• presenting
• visualizing
• writing

​Students are strongly encouraged to consult these resources to help them succeed in the course.

Description & Objective

The primary objective of this course is to introduce you to descriptive and inferential data analysis techniques. These techniques include the chi-square test for independence, the t-test, the analysis of variance (ANOVA), and correlation and regression. If time permits, we will review forecasting techniques.
 
Although various analytical techniques are available, the selected techniques represent tools used most frequently by marketing and management professionals. The tools you learn in the course go beyond simple data descriptors, including description, variability, and location measures. Such descriptors serve as a starting point for us to explore the data set. Techniques learned in this course will allow you to make a more informed decision and recommendation.
 
Data analysis represents a critical thinking tool. As consumers of knowledge, you will need to assess whether you have good or not-so-good knowledge. By understanding data analysis, you can determine whether the analysis is appropriate and whether you have good knowledge.
 
Finally, these data analysis techniques represent a more robust approach to understanding data. As producers of knowledge, you can furnish a more sophisticated analysis, which should establish your value to the firm and, in turn, help the firm be more efficient and/or effective.