Statistical Data Modeling in Business Analytics I

In this hands-on course, you will focus on the appli­ca­tion of fit­ting sim­ple sta­tis­ti­cal mod­els to data and exper­i­ments. The dif­fer­ence between descrip­tive and infer­en­tial sta­tis­tics will be dis­cussed, with the intro­duc­tion of prob­a­bil­i­ty and data dis­tri­b­u­tions. You will then fit sim­ple mod­els to data start­ing with sim­ple lin­ear regres­sion, mul­ti­ple lin­ear regres­sion and analy­sis of vari­ance. By the end of the course, you should be able to inter­pret sta­tis­ti­cal mod­els of how to report them. Pre­req­ui­site EXGEN 5449
Course at a glance
  • Aimed at mid-level managers who are involved with data analysis and the analytics needs within their organization.
  • In-class, face-to-face delivery.
  • A hands-on, experiential course based on short lectures, discussions, and plenty of in-class exercises using R.
What you will learn

By the end of this course, you should be able to:

  • Have a basic understanding of statistical concepts: descriptive vs. inferential statistics, sampling and probability distributions, and experimental design.
  • Use the R programming language for statistical computing to carry out basic statistical analyses: correlation; simple linear regression; one sample, two sample; and paired t-tests.
  • Visualize and interpret statistical output.
  • Understand the meaning of statistical output.
  • Visualize results in a publication-ready format.
  • Acknowledge the limitations of the results.
Take note:

  • All course resources and learning materials are provided in-class.
  • Students are required to bring a laptop; R and R Studio will be downloaded in class.
  • This is an attendance-basis, non-graded course.
When will
this course be offered?

New course schedules are released each June and November.

Course not yet scheduled

This course is not currently scheduled, but may be offered in an upcoming term.

New course schedules are announced each June and November.

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