Quantitative Analysis III
CIT 32000/ 3 Cr.
A continuation of statistical inference introduced in Quantitative Analysis II with emphasis on confidence intervals, hypothesis testing, analysis of variance, forecasting, including linear regression and correlation, and quality control as they apply to information technology.
- Available Online: No
- Credit by Exam: No
- Laptop Required: Yes
P: CIT 22000.
Course Outcomes(What are these?)
- Enhance student quantitative reasoning skills through a study of inferential statistics (CIT a)
- Improve students ability to express situations in mathematical terms and to design analytical experiments (CIT i)
- Develop student awareness of how and when to make quantitative assumptions and simplification (CIT a)
CIT Student Outcomes(What are these?)
(a) An ability to apply knowledge of computing and mathematics appropriate to the program’s student outcomes and to the discipline.
(i) An ability to use current techniques, skills, and tools necessary for computing practice.
- Hypothesis Testing-One Sample Tests
- Hypothesis Testing-Two Sample Tests
- Chi-Square and Analysis of Variance
- Simple Regression Analysis and Correlation
- Time Series and Forecasting
Principles of Undergraduate Learning (PULs)
1b. Identify and propose solutions for problems using quantitative tools and reasoning.
1c. Make effective use of information resources and technology.
3. Integration and Application of Knowledge
4. Intellectual Depth, Breadth, and Adaptiveness