MIS G1010: Statistics and Decision Making
The objective of this course is to help you learn to analyze data and use methods of statistical inference in making business decisions. This course will focus on the application of fundamental concepts covered in Probability and Decision Making to the problem of drawing inferences from data on observed outcomes. Topics covered during the first part of the course will include statistical sampling and sampling distributions, point estimation and confidence intervals, hypothesis testing, and correlations among variables. The second part of the course will focus on multivariate analysis, with special attention paid to the inferences that may drawn with respect to prediction and causality.
- Syllabus
- Assignments
- Projects
- Lecture 1
- Statistics and Variation
- Variable Types
- Surveys and Sampling
- Sampling Designs
- Bad Sampling
- Displaying and Describing Categorical Data
- Lecture 2
- Lecture 3
- Lecture 4
- Lecture 5
- Lecture 6
- Lecture 7
- Lecture 8
- Lecture 9
- Lecture 10
- Lecture 11
- The Multiple Regression Model
- Assumptions and Conditions for the Multiple Regression Model
- Testing the Multiple Regression Model
- Multiple Regression Variation Measures
- Lecture 12
- Time Series
- Smoothing Methods
- Multiple Regression-based Models
- Choosing a Time Series Forecasting Method
- Lecture 13