About this course: This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. The course aim to cover statistical ideas that apply to managers. We will consider two basic themes: first, is recognizing and describing variations present in everything around us, and then modeling and making decisions in the presence of these variations. The fundamental concepts studied in this course will reappear in many other classes and business settings. Our focus will be on interpreting the meaning of the results in a business and managerial setting. While you will be introduced to some of the science of what is being taught, the focus will be on applying the methodologies. This will be accomplished through use of Excel and using data sets from many different disciplines, allowing you to see the use of statistics in very diverse settings. The course will focus not only on explaining these concepts but also understanding the meaning of the results obtained. Upon successful completion of this course, you will be able to: • Test for beliefs about a population.. • Compare differences between populations. • Use linear regression model for prediction. • Learn how to use Excel for statistical analysis. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.
Created by: University of Illinois at Urbana-Champaign
Taught by: Fataneh Taghaboni-Dutta, Clinical Professor of Business Administration
University of Illinois, Urbana-Champaign College of Business Department of Business Administration
| Basic Info | Course 6 of 7 in the Managerial Economics and Business Analysis Specialization |
| Commitment | 4 weeks of study, 2-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Course Orientation
In the course orientation, you will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.
2 videos, 6 readings, 1 practice quiz
- Video: Welcome to Inferential and Predictive Statistics for Business!
- Reading: Syllabus
- Reading: About the Discussion Forums
- Reading: Glossary
- Practice Quiz: Orientation Quiz
- Reading: Using Excel for this Course
- Video: Excel Data Analysis Toolpak
- Reading: Updating Your Profile
- Discussion Prompt: Getting to Know Your Classmates
- Reading: Social Media
Module 1: Hypothesis Testing
Watch any infomercial and you hear many outrageous promises. Use this cream and your skin will look 80% firmer! Use this supplement and you will lose 10 pounds in the first 10 days! Are they telling you the truth? Are they all lying? The only way to know the answer to any of these questions is to scientifically test the claim being made – that is what we call hypothesis testing and what we will learn in this module.
11 videos, 2 readings, 5 practice quizzes
- Reading: Module 1 Overview
- Reading: Module 1 Readings
- Video: 1-1.1. Formulating the Hypothesis
- Practice Quiz: Lesson 1-1 Practice Quiz
- Video: 1-2.1. Analyzing the Result
- Practice Quiz: Lesson 1-2 Practice Quiz
- Video: 1-3.1. Two-Tail Test for Mean
- Video: 1-3.2. Two-Tail Test for Mean in Excel
- Practice Quiz: Lesson 1-3 Practice Quiz
- Video: 1-4.1. One-Tail Test for Mean
- Video: 1-4.2. Left-Tail Test for Mean in Excel
- Video: 1-4.3. Right-Tail Test for Mean in Excel
- Practice Quiz: Lesson 1-4 Practice Quiz
- Video: 1-5.1. Testing the Proportion
- Video: 1-5.2. Left-Tail Test for Proportion in Excel
- Video: 1-5.3. Right-Tail Test for Proportion in Excel
- Video: 1-5.4. Two-Tail Test for Proportion in Excel
- Practice Quiz: Lesson 1-5 Practice Quiz
Graded: Module 1 Quiz
WEEK 2
Module 2: Statistical Inference Based on Two Samples
Does the medicine a person is taking to treat his condition really work better than a sugar pill? Is the new chip-enabled credit card more secure than the magnetic card? How do you know whether the claims being made about anything being “better than” or “faster than” a competitor are true? In this module we will learn to make this comparison.
11 videos, 2 readings, 5 practice quizzes
- Reading: Module 2 Overview
- Reading: Module 2 Readings
- Video: 2-1.1. Testing for No Difference in Means
- Video: 2-1.2. Testing for No Difference in Means in Excel
- Video: 2-1.3. Two-Tail Mean Test for Two Samples and Calculating the Confidence Interval in Excel
- Practice Quiz: Lesson 2-1 Practice Quiz
- Video: 2-2.1. One-Tail Test of the Means
- Video: 2-2.2. One-Tail Test of the Means in Excel
- Practice Quiz: Lesson 2-2 Practice Quiz
- Video: 2-3.1. Testing for a Specific Value in Means
- Practice Quiz: Lesson 2-3 Practice Quiz
- Video: 2-4.1. Paired Tests
- Video: 2-4.2. Paired Test in Excel
- Practice Quiz: Lesson 2-4 Practice Quiz
- Video: 2-5.1. Test of Proportions
- Video: 2-5.2. One-Tail Test of Proportions for Two Samples in Excel
- Video: 2-5.3. Two-Tail Test of Proportions for Two Samples in Excel
- Practice Quiz: Lesson 2-5 Practice Quiz
Graded: Module 2 Quiz
Graded: Inferential and Predictive Statistics Peer Review Assignment
WEEK 3
Module 3: Simple Linear Regression
Does your job involve a lot of sitting? If so, you are at higher risk of coronary heart disease. How do I know this? We got to know the relationship between coronary heart disease and sitting when researchers studied a cohort of London bus drivers and bus conductors from 1947 to 1972. If you want to know more, then read on!
9 videos, 2 readings, 5 practice quizzes
- Reading: Module 3 Overview
- Reading: Module 3 Readings
- Video: 3-1.1. An Introduction
- Practice Quiz: Lesson 3-1 Practice Quiz
- Video: 3-2.1. Least Square Methods
- Video: 3-2.2. Least Square Method in Excel
- Practice Quiz: Lesson 3-2 Practice Quiz
- Video: 3-3.1. Assessing the Regression Model
- Video: 3-3.2. Testing the Significance in Excel
- Practice Quiz: Lesson 3-3 Practice Quiz
- Video: 3-4.1. Using the Model
- Video: 3-4.2. Simple Linear Regression: Excel Output Analysis
- Practice Quiz: Lesson 3-4 Practice Quiz
- Video: 3-5.1. Model Assumptions and Limitations
- Video: 3-5.2. Residual Analysis in Excel
- Practice Quiz: Lesson 3-5 Practice Quiz
Graded: Module 3 Quiz
WEEK 4
Module 4: Multiple Linear Regression
You are trying to predict next month’s sales numbers. You know that dozens, maybe even hundreds, of things like the weather, competitor’s promotions, rumors, etc. can impact the number. You talk to five people and each one has an idea about what makes the biggest impact, and the only thing they offer is “trust me.” Do you wish there was a better way of doing this rather than relying on blind faith? Well, there is. We can use Multiple Regression to sort through this mess and bring the focus to factors that really do matter.
7 videos, 2 readings, 3 practice quizzes
- Reading: Module 4 Overview
- Reading: Module 4 Readings
- Video: 4-1.1. Model Introduction
- Video: 4-1.2. Developing Multiple Regression Model in Excel
- Video: 4-1.3. Multiple Regression: Excel Output Analysis
- Practice Quiz: Lesson 4-1 Practice Quiz
- Video: 4-2.1. Qualitative Data – Two Categories
- Video: 4-2.2. Dummy Variable in Excel – Two Categories
- Practice Quiz: Lesson 4-2 Practice Quiz
- Video: 4-3.1. Qualitative Data – Many Categories
- Video: 4-3.2. Dummy Variable in Excel – Many Categories
- Practice Quiz: Lesson 4-3 Practice Quiz
Graded: Module 4 Quiz
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Pricing
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| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
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Ratings and Reviews
thanks
Excellent course taught by wonderful professor.
Very good introductory Statistics course. The topic selection is very pertinent to meet the need of a manager to analyze data and to make decision. Quality of teaching is GREAT.
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DK
Great course for decision makers with no prior experience in statistics and modelling. Lots of real life examples used to illustrate the steps needed to build a model that could predict and explain ones data. Step by step examples in Excel make the life easy for those with no math background in statistical calculations. I liked the professor's focus on the interpretation of the models' results.