Biological Sciences)

Descriptive statistics, displaying and summarizing data, probability and its role in statistical modeling and inference; comparing several groups of data; exploratory data analysis; point and interval estimates; linear models; analysis of variance and linear regression. This course provides an introduction to the basic ideas of applied statistics with examples and applications focused in the social sciences. This course covers analysis of univariate and multivariate data, linear regression and analysis of variance, with an emphasis on graphical displays. Commonly used probability distributions, such as normal and binomial, are introduced as useful models for observed data. Students are required to use statistical software, minitab recommended. Examples emphasize applications in Psychology/Biological Sciences.

Duke University
Spring 2000
MW, 2:20PM- 3:35PM (6th Period)
Room 111 Biological Sciences Building

Instructor: Brani Vidakovic

Office: 223 B Old Chemistry Building

Office Hours: Tuesdays 2:15-3:30; Thursdays 2:15-3:30

Phone: 684-8025

Email: brani@stat.duke.edu

Instructor:	Brani Vidakovic
	Office: 223 B Old Chemistry Building
	Office Hours: Tuesdays 2:15-3:30; Thursdays 2:15-3:30
	Phone: 684-8025
	Email: brani@stat.duke.edu

Teaching Assistants:

Name Email Phone Office Hours Office Location

Prachi Thakar prachi@cs.duke.edu 660-4003 by appointment N-3 North Building

German Molina Calvo german@stat.duke.edu 684-8840 by appointment 222 Old Chem

Name	Email	Phone	Office Hours	Office Location
Prachi Thakar	prachi@cs.duke.edu	660-4003	by appointment	N-3 North Building
German Molina Calvo	german@stat.duke.edu	684-8840	by appointment	222 Old Chem

Recitations:

Section Teaching Asst Time Room/Bldg

1 German W, 8:00 AM- 8:50 AM Teer 106

2 Prachi Th, 9:10 AM- 10:00 AM Teer 106

3 German F, 9:10 AM- 10:00 AM Teer 106

4 Prachi F, 10:30 AM- 11:20 AM Teer 106

Section	Teaching Asst	Time	Room/Bldg
1	German	W, 8:00 AM- 8:50 AM	Teer 106
2	Prachi	Th, 9:10 AM- 10:00 AM	Teer 106
3	German	F, 9:10 AM- 10:00 AM	Teer 106
4	Prachi	F, 10:30 AM- 11:20 AM	Teer 106

Text: Introductory Statistics, By Prem S. Mann Third Edition, John Wiley & Sons, ISBN 0-471-16546-8

Groups: Students are encouraged to form small (up to 4 people) learning/working groups. Homeworks and the Final Project are group assignments.

Final Project: Each group will work on one research project. The project is presented to the instructor and fellow students in class, on Wednesday 4/26/2000. Details on format of the project - in class.

Quizzes: Weekly quizzes during recitation classes; lowest quiz score will be dropped -- no make-ups.

Homework: Homeworks are weekly group assignments.

Final: The final exam will be open book, open notes and will be comprehensive [will test material from the entire semester].

Grading: Course grade is based on the midterm (20%), quizzes and homeworks (15+15%), final project (20%) and final (30%) .

Tentative Outline Syllabus:

W(M) Jan 12: Introduction to the course; Data; Some examples of statistical thinking. HW1; 2.19; 2.37; 2.50; 4 (page 78); M1.1; M1.2;

W Jan 19: Minitab Software. Descriptive Statistics;

M Jan 24: HW1 due. Descriptive measures; HW2: 3.24; 3.65; 3.79; 3.82; 3.94; 3.106; M3.4; M3.7

W Jan 26: Class was cancelled.

M Jan 31: HW2 postponed for Wednesday Descriptive measures. Probability. Read Chapter 4. HW3: 4.37; 4.58; 4.92; 4.97; 4.126; 4.139; 4.140;

W Feb 2: Probability; HW2 due. Read Chapter 4.

M Feb 7: HW3 due. Bayes Formula. Discrete Random Variables. HW4: 5.14; 5.31; 5.56; 5.60; 5.98; M5.1; M5.4; Read Chapter 5.

W Feb 9: Discrete random variables. Bernoulli and Poisson distribution. Read Chapter 5.

M Feb 14: HW4 due. Continuous probability distributions. Normal Distribution. HW5: 6.25; 6.36; 6.49; 6.58; 6.61; 6.64; 6.78; M6.2 ; M6.4 Read Chapter 6.

W Feb 16: Normal approximation to Bernoulli distribution. Read Chapter 6.

M Feb 21: HW5 due. Central Limit Theorem. Sampling distributions. Estimators. HW6: 7.9; 7.10; 7.11; 7.64; 7.66; 7.88; 7.89; M7.1; M7.2 Read Chapter 7.

W Feb 23: Proportions. Read Chapter 7.

M Feb 28: HW6 due. Interval estimation of the mean. HW7: 8.19; 8.24; 8.25; 8.51; M8.1; M8.6 Read Chapter 8.

W Mar 1: Proportions. Sample size design. About the midterm. Read Chapter 5.

M Mar 6: HW7 due. MIDTERM.

W Mar 8: Midterm back. Discussion of problems from the midterm. Bayesian Estimation (handout)

M Mar 20: Testing hypotheses about the mean. HW8: 9.35; 9.64; 9.69; 9.113, M9.2; M9.4; M9.6 M96 need the following macros: pinf.MTB , pinft.MTB , pinft1.MTB , pinft2.MTB , and pinft3.MTB . Read Chapter 9.

W Mar 22: Testing the proportion; Small samples; p-values; Applications. Read Chapter 9.

M Mar 27: HW8 due. Two populations. Cpmparisons of means and proportions. HW9: 10.14; 10.18; 10.33; 10.35; 10.47; 10.55; 10.59; 10.73; M10.1; M10.3; M10.5. Read Chapter 10.

W Mar 29: Two populations; Paired Samples. Read Chapter 10.

M Apr 3: HW9 due. Chi-square theory. Goodness-of-fit. Tests and confidence interval for population variance. HW10: 11.18; 11.19; 11.30; 11.71; 11.74; M11.1; M11.3 Read Chapter 11.

W Apr 5: Chi-square theory. Contingency tables: Testing for independence or homogeneity. Read Chapter 11.

M Apr 10: HW10 due. Correlation. Regression Problem. HW11: 13.30; 13.45; 13.52; 13.79; 13.81; 13.92; 13.107; M13.1 Read Chapter 13.

W Apr 12: Regression; inference about tha parameters. Read Chapter 13.

M Apr 16: SNOW-MAKEUP DAY Discussion about FINAL PROJECTS

M Apr 17: HW11 due. Regression; Multivariate; general models; HW 12: 12.14; 12.15; 12.18; 12.26; M12.1; M12.2. Read Chapter 12.

W Apr 19: ANOVA; F-distribution; Applications; Read Chapter 12.

M Apr 24: HW12 due. ANOVA 2 way; Block design. Contrasts. Read Chapter 12.

W Apr 26: Preparation for the final

Please send comments to brani@stat.duke.edu