QM 67000: Business Analytics

Mitch. Daniels School of Business, Purdue University


IMPORTANT

This document does not replace the official information in the course brightspace page


Course Description and Objectives

This course develops the quantitative and data-analysis skills managers need to make data-driven decisions. Coverage includes descriptive statistics, probability and probability distributions, decision analysis, sampling distributions and interval estimation, hypothesis testing, and applied regression analysis (simple and multiple).

Our primary goal is to instill the quantitative and data-analysis skills essential in modern business, where Business Analytics and Data Science are increasingly important. These skills empower managers to make data-based decisions, perform risk assessments, develop policies, and collaborate effectively with analytics teams to improve business performance.

The course uses an active-learning approach built around realistic business cases. In each class you take the manager’s seat: you evaluate an analyst’s work, reproduce it yourself, stress-test it, and make the call.

The course is Excel-first: every method is demonstrated in Microsoft Excel with the Analysis ToolPak, the standard tool for the analyses we cover.

Course Website: https://davi-moreira.github.io/2026F_business_analytics_qm670/

Meets: Check the Course Brightspace page for details.

Instructor: Professor Davi Moreira

  • Office: Young Hall 1019
  • Email: dcordeir@purdue.edu
  • Office hours: Check the Course Brightspace page for details.
  • Individual Appointments: Check the Course Brightspace page for details.

Learning Outcomes

By the end of this course, students will be able to:

  1. Understand basic statistical principles and their applications in management and business.
  2. Understand fundamental issues in business and management, and translate them into statistical questions.
  3. Describe and use commonly used statistical techniques for analyzing business data, and interpret the results for a decision-maker.
  4. Be proficient in using Excel to carry out the statistical and analytics methods covered in the course.

Prerequisites

This is an entry-level graduate analytics course. Comfort with basic spreadsheet use is helpful but not required; we build the analytical tools from the ground up.

Course Materials

  • Textbook:
    Anderson, Sweeney, Williams, Camm, and Cochran.
    Statistics for Business and Economics, 14th Edition, Cengage Learning, Inc. (ISBN-13: 978-1337901062), referred to as SBE.

  • Handouts:
    Lecture Slides and Supplementary Materials (available on Brightspace).
    The E-Book and handouts are located in Brightspace → Content → Table of Contents → …

  • Computing:
    Bring a laptop (PC, Mac, or tablet) to every class for in-class practice exercises and group cases.

  • Software:
    Microsoft Excel is used for in-class demonstrations. Ensure the “Data Analysis” ToolPak is enabled:

    1. File -> Options -> Add-ins
    2. Select Analysis ToolPak and Analysis ToolPak-VBA → Go
    3. Data → Data Analysis (for Excel-based analyses)

Course Infra-structure

Brightspace: The Course Brightspace Page https://purdue.brightspace.com/ should be checked on a regular basis for announcements and course material.

Software: Microsoft Excel will be used for in-class demonstrations and instruction. The main tool is Data Analysis under Tools. If you don’t see this tool, follow the following steps to add in:

  • File -> Options -> Add-ins -> Select Analysis ToolPak and Analysis ToolPak-VBA (also select StatTools 7.5, if available) -> Go -> Data -> Data Analysis (to conduct analyses)

Course Website: This class website will be used throughout the course, but it does not replace the Course Brightspace Page.