Schedule and Textbooks Information

Spring 2023 Schedule and Textbook Information for STAT 113

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STAT 113 - Textbook(s) for Spring 2023

CRN	Title	Author	ISBN	Version	Req/Opt
ALL	Concepts and Controversies	David S. Moore, William Notz	9781319109028	10th	Y

STAT 113 - Schedule information for Spring 2023

CRN	Section	Instructor	Day	Time	Room
16948	205	Cheryl Crabill		0:0-0:0am	ASYNC ONLINE
27712	100	Cheryl Crabill	TR	10:30-11:20am	MTHW 210
27713	200	Cheryl Crabill	TR	08:30-09:20am	MATH 175
36934	032	Evan Li	M	12:30-1:20pm	SCHM 314
27723	052	Phalguni Nanda	M	08:30-09:20am	SCHM 103
27721	082	Phalguni Nanda	M	09:30-10:20am	SCHM 103
27725	093	Phalguni Nanda	M	11:30am-12:20pm	SCHM 103
15847	201	Ziyi Wang	M	2:30-3:20pm	SCHM 103
15850	204	Ziyi Wang	M	11:30am-12:20pm	SCHM 314
27728	033	Ziyi Wang	M	10:30-11:20am	SCHM 314
52986	072	Evan Li	M	2:30-3:20pm	SCHM 314
15849	203	Evan Li	M	3:30-4:20pm	SCHM 314
27732	062	Daniel Cardona	M	12:30-1:20pm	SCHM 103
27737	002	Wenjie Li	M	3:30-4:20pm	SCHM 103
27735	001	Wenjie Li	M	4:30-5:20pm	SCHM 103
15848	202	Wenjie Li	M	1:30-2:20pm	SCHM 314
27717	083	Daniel Cardona	M	10:30-11:20am	SCHM 103
27742	091	Daniel Cardona	M	1:30-2:20pm	SCHM 103

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.