Schedule and Textbooks Information

Spring 2022 Schedule and Textbook Information for STAT 113

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STAT 113 - Textbook(s) for Spring 2022

CRN	Title	Author	ISBN	Version	Req/Opt
27712	Statistics Concepts and Controversies	David S. Moore, William I. Notz	9781319109028	10th	Y
27713	Statistics Concepts and Controversies	David S. Moore, William I. Notz	9781319109028	10th	Y
60331	Statistics Concepts and Controversies	David S. Moore, William I. Notz	9781319109028	10th	Y

STAT 113 - Schedule information for Spring 2022

CRN	Section	Instructor	Day	Time	Room
27713	200	Cheryl Crabill	TR	08:30-09:20am	FRNY G140
27712	100	Cheryl Crabill	TR	09:30-10:20am	FRNY G140
27737	002	Evan Li	M	1:30-2:20pm	REC 314
27728	033	John Lambrecht	M	11:30am-12:20pm	UNIV 319
27717	083	John Lambrecht	M	1:30-2:20pm	REC 103
27725	093	John Lambrecht	M	10:30-11:20am	UNIV 319
19535	208	Ziyi Wang	M	08:30-09:20am	BRNG 1206
19532	207	Ziyi Wang	M	11:30am-12:20pm	BRNG 1248
27735	001	Ziyi Wang	M	09:30-10:20am	BRNG 1206
27723	052	Mudit Gaur	M	2:30-3:20pm	UNIV 319
15848	202	Mudit Gaur	M	3:30-4:20pm	UNIV 319
19527	206	Mudit Gaur	M	12:30-1:20pm	BRNG 1248
27742	091	Xinyi Pei	M	3:30-4:20pm	REC 103
15850	204	Evan Li	M	2:30-3:20pm	REC 314
27721	082	Evan Li	M	4:30-5:20pm	BRNG B206
36934	032	Wenjie Li	M	11:30am-12:20pm	BRNG 1206
15847	201	Wenjie Li	M	10:30-11:20am	BRNG 1206
15849	203	Wenjie Li	M	08:30-09:20am	BRNG B243
52986	072	Xinyi Pei	M	2:30-3:20pm	REC 103
27732	062	Xinyi Pei	M	12:30-1:20pm	UNIV 319

STAT 113 - Course Outline

1. Collecting Data
   
   
   1. Sampling: random samples; use of tables of random digits; sources of bias in sampling human populations; multistage and stratified samples; random selection as public policy.
      Applications: Opinion polling, TV ratings, government economic and social statistics.
   
   
   
   2. Design of experiments: randomized comparative experiments; blocking and other elaborations; ethics of experimentation on human subjects.
      Applications: medical experiments, social policy experiments.
   
   
   
   3. Measurement: bias, reliability and validity; scales of measurement; good and bad data.
      Applications: measuring unemployment, critiquing the use of data in persuasion.
   
   
   
2. Organizing and Describing Data
   
   
   1. Tables and graphs: bivariate frequency tables; common graphs and their abuses; frequency distributions; the normal distributions.
   
   
   
   2. Numerical summary measures: mean, median, mode; percentiles and boxplots; standard deviation and variance; correlation and regression; the question of causation.
      Applications: smoking and health, standardized tests as predictors.
   
   
   
   3. Index numbers and related topics: index numbers, interpretation of time series data.
      Applications: The Consumer Price Index; national economic indicators; social indicators.
   
   
   
3. Formal Statistical Reasoning
   
   
   1. Probability: what is probability; simulation using random digits; expected values and the law of large numbers.
      Applications: state lotteries.
   
   
   
   2. Confidence intervals: basic ideas, simulations.
      Applications: return to opinion polling.