Prerequisites

CIT 22000

Offered

Spring

Software

SPSS

Credit By Exam

No

Coordinator

E. Fernandez

What you will learn

Description

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.

Textbook

McClave & Sincich, Statistics, Prentice Hall, 2006, ISBN 0131497553

Holcomb, SPSS Basics, Pyrczak Publishing, ISBN 1884585671

Course Outcomes

• Enhance student quantitative reasoning skills through a study of inferential statistics (CIT 1)
• Improve students ability to express situations in mathematical terms and to design analytical experiments (CIT 9)
• Develop student awareness of how and when to make quantitative assumptions and simplification (CIT 3)

CIT Program Outcomes (What are these?)

1. Demonstrate mastery of core computing and mathematical concepts.

3. Plan, design, implement, and evaluate IT-based projects and systems to meet desired needs.

9. Use current technical concepts, techniques and practices in the information technologies within the student"s area of expertise.

Principles of Undergraduate Learning (What are Principles of Undergraduate Learning?)

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

Topics

• 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

Assessment

• Exams
• Homework
• Participation