Syllabus
CSC 323 - Data Analysis and Statistical Software

Joseph A. Morgan
Office: CT&I 210
Phone: (312) 362-6321
Email: jmorgan@cs.depaul.edu

Texts.

• Required: (SAS) SAS System for Elementary Statistical Analysis. Schlotzhauer & Littell. SAS, 2nd edition, 1997.
• Optional: (FPP) Statistics. Freedman, Pisani, and Purves. Norton, 3rd edition, 1998.

Schedule - Quizzes/Midterm/Final.

1. Review/Introduction
2. Quiz #1; Program #1 given
3. Quiz #2
4. Quiz #3; Program #1 due
5. Midterm; Program #2 given
6. Quiz #4
7. Quiz #5; Program #2 due
8. Quiz #6; Program #3 given
9. Quiz #7
10. Program #3 due
11. Final

Grading.

Grades will be determined from percentage of total points earned on a series of quizzes and on programming assignments. A quiz will be given in most classes. The final exam will consist of the equivalent of about three quizzes and is required. The lowest quiz score (not counting the final quizzes) will be dropped. Makeup quizzes will not be given.

The grade breakdown will be as follows:

• Programming Assignments : 20%
• Quizzes : 40%
• Midterm : 15%
• Final : 25%

Cutoffs for grades will be no higher than the following: 90-100, A; 80-89.99, B; 70-79.99, C; 60-69.99, D; 0-59.99, F. Pluses and minuses will be given at the high/low ends of each grade range (no A+'s or D-'s).

Topics.

• Introduction:
  Terminology. Descriptive statistics. Modeling populations - the Normal distribution. Preliminary SAS topics - the SAS system.
  Readings: SAS Chapters 2-5 (skip pp88-92, pp112-117 & pp145-155) and optionally FPP Chapter 4.1, 4.2, 4.6 & 5

• Sampling Distributions, Confidence Intervals and Hypothesis Testing:
  Expected value, standard error, and the Normal distribution. Sample surveys. Chance errors in sampling. The accuracy of proportions and means. A model for measurement error. Confidence intervals and simple hypothesis testing for the population mean and proportion (and possibly other parameters). SAS functions for simple hypothesis testing.
  Readings: SAS Chapter 5, pp149-155 & Chapter 6, pp 163-178.

• Correlation and Regression:
  Definitions and explanation of these two related concepts. Estimates of slope and intercept. The simple regression model, its parameters and assumptions. Conducting a residual analysis to assess these assumptions. SAS functions for correlation and regression.
  Readings: SAS Chapters 9-10 (skip pp298-303, pp306-324, pp343-352 & pp357-361) and optionally FPP Chapter 7, 8, 9, 11 & 12

Plagiarism/Cheating:

Incompletes: