Introduction to Statistics 1

Introduction to Statistics 1 357a 2 Credits
Introduction to Statistics 1/Honors 357b 2 Credits

THIS COURSE IS APPROPRIATE TO TAKE AT ANY POINT IN A STUDENT?S HIGH SCHOOL MATH SEQUENCE AFTER ALGEBRA II.

PREREQUISITE: A MINIMUM OF C- IN ALGEBRA II OR IMP 3 OR CONFERENCE WITH DEPARTMENT HEAD.

Did you ever wonder what you can really know from a set of data or statistics about, say, racial profiling or global warming? This course begins with an in-depth study of variability, in particular categorizing and quantifying different sources of variability in a data set. Topics include: Measurement variation, natural variation, production variation, sample variation, data and probability distributions, and measures of center and dispersion. These concepts are then applied to the analysis of bivariate data sets: correlation, residuals and least-squares lines, and linear and non-linear model fitting. Emphasis is placed on assessing the predictive value of the models. This course challenges students to analyze real data and confront the assumptions, power and limits of statistical analysis. The course makes extensive use of Fathom data analysis software. Students analyze data, prepare reports and make presentations of their findings throughout the course.

Possible Next Courses: Introduction to Statistics 2, Trigonometry 

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