Course Description
Sampling and statistical studies; basic probability; random variables and their distributions; exploring data using graphical techniques and numerical summaries; exploring relationships between two variables: chi-sq. test of independence; correlation, linear regression; confidence intervals and hypothesis testing for means and proportions. Group projects and activities illustrating concepts will be utilized.
Additional Requirements for Graduate Students:
Additional problems of a more in-depth nature will be required for graduate students.
Athena Title
Statistics for Secondary Teach
Equivalent Courses
Not open to students with credit in STAT 4050, EMAT 4050 or STAT 6050, EMAT 6050
Prerequisite
STAT 2000
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
The goals of this course are twofold. First, the course will present statistical techniques for collecting and analyzing data with an emphasis on statistical thinking and how statistics is used in everyday situations. Students will learn how to read data summaries critically, how to produce data, how to use sound and appropriate methods for drawing trustworthy conclusions, how to make defensible descriptions and inferences about samples and populations, how to design experimental studies, how to distinguish between observational and experimental studies, and how to communicate the appropriate conclusions of statistical studies (both orally and written). The second goal of the course is to enhance the quality of training for secondary mathematics teachers (both pre-service and in-service) so that they will be better prepared to develop and teach statistics courses at the Pre-K-12 grade level, especially AP Statistics. Toward this end, secondary mathematics teachers will be introduced to and trained in modern technological resources for classroom instruction including statistical software and statistical calculators.
Topical Outline
Course topics include summarizing and exploring data for both univariate (histograms, stem and leaf plots, boxplots, dotplots, timeplots, measures of location, measures of dispersion, z-scores, Empirical Rule) and bivariate analysis (scatterplots, correlation, regression, contingency tables, conditional proportions); study design, including sampling techniques for surveys, and the design of experimental and observational studies; probability and probability distributions, including the binomial and normal; sums of random variables; sampling distributions; confidence intervals for means and proportions; significance testing for means and proportions; Type I and II errors; power of a test; chi-square tests and related methods for contingency tables; and linear regression, including simple and multiple linear regression, inference in regression, and residual analysis.
Syllabus