Daniel Caraway

Daniel Caraway

I put the fun in functions.

MSDS MBC638: Data Analysis and Decision Making

3 minute read

Data Analysis and Decision Making

MSDS (MBA) - Q1: MBC638 (2018-0629)

Description:

This course will familiarize students with the assumptions underlying various statistical techniques and assist in identifying their appropriateness in a variety of situations. The student should be able to perform statistical analysis and interpret results in a meaningful way. Students are expected to relate results of such analyses to become an information-based decision maker.

Learning Goals

  • Help students understand the value of data collection and analysis in acquiring knowledge and making decisions in today’s business environment.
  • Students will be able to identify and apply the appropriate statistical technique for a given set of conditions in order to answer a particular question.

Deliverables:

Class Outline:

Assignments and Deliverables

  • Week 1: Problem Definition Worksheet
  • Week 2: Quiz 1
  • Week 3: Homework 1
  • Week 4: Homework 2
  • Week 5: Homework 3
  • Week 6: Quiz 2
  • Week 7: Homework 4
  • Week 8: Homework 5
  • Week 9: Homework 6
  • Week 10: Process Improvement Project
  • Week 10: Final Exam Quiz
  • Participation

Week 1 | Fundamentals

  • 1.1 Week 1 Introduction
  • 1.2 Week 1 Readings
  • 1.3 Fundamentals of Statistics and DMAIC
  • 1.4 Types of Data: Pros and Cons
  • 1.5 Exercise: What Type of Data?
  • 1.6 Sigma Quality Level (SQL)
  • 1.7 Operational Definitions
  • 1.8 Soft Tools
  • 1.9 The Kappa Technique
  • 1.10 Peanut Exercise

Week 2 | Business Process

  • 2.1 Week 2 Introduction
  • 2.2 Week 2 Readings
  • 2.3 Hank the Handyman
  • 2.4 Analyzing the Current Process
  • 2.5 Hank the Handyman: Mapping the Process
  • 2.6 Hank the Handyman: Describing the Data
  • 2.7 Hank the Handyman: Improving the Process

Week 3 | Probability Distributions and Hypothesis Testing

  • 3.1 Week 3 Introduction
  • 3.2 Week 3 Readings
  • 3.3 Common Distributions and CLT with Dice
  • 3.4 Normal Distribution Examples
  • 3.5 Binomial Distribution Examples
  • 3.6 Using Excel to Calculate Probabilities
  • 3.7 Writing Hypothesis Statements
  • 3.8 H0 and Ha Scenarios
  • 3.9 Types of Hypothesis Tests
  • 3.10 More Hypothesis Testing and the Risk of Being Wrong
  • 3.11 Alpha vs. Beta
  • 3.12 Project Hypothesis Statements

Week 4 | Categorical Data Analysis

  • 4.1 Week 4 Introduction
  • 4.2 Week 4 Readings
  • 4.3 Chi-Square Test of Independence: What Is It?
  • 4.4 Chi-Square Example
  • 4.5 Chi-Square Test for Independence in Excel
  • 4.6 Test Your Knowledge: Gender Differences at the Coffee Shop
  • 4.7 Relate Chi-Square to Your Project

Week 5 | Confidence Intervals and Sample Size

  • 5.1 Week 5 Introduction
  • 5.2 Week 5 Readings
  • 5.3 Confidence Intervals for Continuous Data
  • 5.4 Confidence Interval Example
  • 5.5 Sample Size for Continuous
  • 5.6 Confidence Interval and Sample Size for Discrete Data
  • 5.7 Test Your Knowledge
  • 5.8 Relate Sample Size to Your Project

Week 6 | Simple Linear Regression and Correlation

  • 6.1 Week 6 Introduction
  • 6.2 Week 6 Readings
  • 6.3 Correlation Video
  • 6.4 Regression Introduction
  • 6.5 Example by Hand
  • 6.6 SLR Examples and Using Excel
  • 6.7 Correlation
  • 6.8 Correlation Using Excel
  • 6.9 Residuals and Other Warnings
  • 6.10 Residuals and Other Warnings Using Excel

Week 7 | Multiple Linear Regression

  • 7.1 Week 7 Introduction
  • 7.2 Week 7 Readings
  • 7.3 Multiple Regression
  • 7.4 Multiple Regression Using Excel
  • 7.5 Correlation, F Test, and Model Building
  • 7.6 Just Correlation
  • 7.7 Categorical Input Variables
  • 7.8 Test Your Knowledge: Categorical Input Variable
  • 7.9 Relate Regression to Your Project

Week 8 | Process Control Charts

  • 8.1 Week 8 Introduction
  • 8.2 Week 8 Readings
  • 8.3 Control Chart Introduction and Types Available
  • 8.4 Control Chart Calculations
  • 8.6 How to Build ImR in Excel
  • 8.7 Using Control Charts as a Proactive Tool
  • 8.8 Test Your Knowledge: Measurement System
  • 8.9 Relate Control Charts to Your Project

Week 9 | Time Series Analysis

  • 9.1 Week 9 Introduction
  • 9.2 Introduction to Time Series
  • 9.3 Autocorrelation
  • 9.4 Is Autocorrelation Present?
  • 9.5 Three Time Series Models
  • 9.6 Forecast the Next Month: First Order Autoregressive
  • 9.7 Forecast the Next Month: Moving Average Model
  • 9.8 Forecast the Next Month: Exponential Smoothing
  • 9.9 Test Your Knowledge: Time Series Models
  • 9.10 Relate Time Series to Your Project

Week 10 | Review and Process Improvement Project Work

  • 10.1 Week 10 Introduction
  • 10.2 Summary of DMAIC
  • 10.3 Questions You Should Be Able to AnswerPage

You may also enjoy