Instructor: Anatolii Grinshpan

Office hours: T 12-1 & R 12-2, Korman 249.

Course information Academic
Calendar Tutoring center John Rice R project Philip
Stark

Jan 6.
Introduction. Measures of
location and measures of dispersion. Simple random
sampling.

Jan
8. Quantiles. Shape parameters.
Empirical frequency function. Histograms, stem-and-leaf plots, QQ plots, boxplots.

Reading:
Ch. 10. Problems: due January 15.

Jan 13.
Sampling with and without replacement. The
distribution of the sample mean. Variance of the
sample mean. Example.

Jan 15.
Order statistics. Covariance calculation. Sample variance. Lagrange identity.
Bessel correction.

Reading:
Ch. 7. Problems: due January 22.

Jan 20.
The distribution of the sample variance. Sampling from normal
distribution. Types of sampling.

Jan 22.
Confidence intervals for the population mean. Point estimation
of parameters. The method of moments. Waiting times.

Reading:
Ch. 7, 8. Problems: due January 29.

Jan 27.
Waiting times. The method of
maximum likelihood. Capture-recapture.

Jan 29.
Sampling from multinomial distribution. Examples of parameter estimation.

Reading:
Ch. 8. Problems.

*Feb 2.
Questions session 1-2 PM (Korman 207).*

Feb 3. Midterm 1 (lectures of Jan 6 – Jan 29).

Feb 5. Hypothesis testing. Example.

Reading: Ch. 9. Problems: due February 12.

Feb 10.
Likelihood ratio test. Chi-square distribution (chi calculator). Student’s
t-distribution (t calculator).

Feb 12.
Hypothesis testing: test statistic, null
distribution, power curve, z-tests and t-tests.

Reading: Ch. 8, 9. Problems: due February 19.

Feb 17.
Bayes vs Neyman-Pearson.
P-values. Confidence intervals and
hypothesis tests. Pearson’s theorem.

Feb 19.
Chi-square test. The
likelihood ratio test for the mean of a normal distribution.

Reading: Ch. 9. Problems: due February 26.

Feb 24. The likelihood ratio test for the mean of a normal distribution.

Feb 26. Dance of the p-values. The generalized likelihood ratio. Multinomial context.

Reading: Ch. 9. Problems.

*Mar 2.
Questions session 11-Noon (Korman
207).*

Mar 3. Midterm 2 (lectures of Feb 5 – Feb 26).

Mar 5. Comparing two samples: z and t tests, paired tests.

Reading: Ch. 11. Problems: due March 12.

Mar 10. Analysis of variance. (F calculator).

Mar 12. Linear least squares. Simple model.

Reading: Ch. 12, 14. Problems.

Mar 17. *Questions session 1-2+ PM, Curtis 344*.

Mar 19. Final exam (all lectures), 8-10 AM, Curtis 344.