MATH 117A - Elements of Statistics

(MATF)

Intended primarily for students who require both an introductory statistics course and a course of intermediate algebra. This course covers introductory statistics topics such as descriptive analysis and treatment of data, probability and probability distributions, linear regression, and tools of statistical inference while also covering the support content from intermediate algebra needed to study these topics and more. Credit may not be earned in both MATH 117 and MATH 117A. Credit may not be earned in both MATH 115A and MATH 117A. Not intended for students with a grade of C or better in MATH 092, MATH 093 or MATH 096 or their equivalent. PREREQUISITE(S): Appropriate score on the mathematics assessment test, a grade of C or better in MATH 080 , or consent of department. Assessment Level(s): ENGL 101 /ENGL 101A or AELW 940 , READ 120 or AELR 930 . For computation of tuition, this course is equivalent to five semester hours. Five hours each week. Formerly MA 116A.

3 semester hours

Course Outcomes:
Upon course completion, a student will be able to:

Calculate and interpret confidence interval estimates of population parameters (proportions and/or means).
Demonstrate an understanding of specific symbolic and graphical characteristics of linear, quadratic, and exponential functions.
Demonstrate an understanding of the importance that random sampling and randomization play in producing data that allow one to draw conclusions about the underlying populations.
Develop the appropriate linear, quadratic, or exponential function model from real world data.
Explain that statistical procedures have specific requirements necessary for their application and verify that the fulfillment of these requirements has been satisfied for the situation with which the student is dealing.
Explain, translate, and solve linear, quadratic, and exponential application problems.
Express in clearly written form, and always in the context of the particular problem situation, the results of statistical investigations and analyses.
Formulate and conduct tests of significance for population parameters (proportions and/or means) and interpret the results in the original context.
Interpret, in context, the key features of linear, quadratic, and exponential functions.
Solve linear, quadratic, and exponential equations by applying algebraic, numerical, and/or graphing techniques.
Use a variety of graphical and numeric tools to explore and summarize categorical and quantitative data, including linear models of associations between two quantitative variables.
Use linear, quadratic, and exponential models to evaluate and make predictions.
Use numerical, verbal, algebraic, or graphical strategies to do all of the above.
Use statistical software (computer- or calculator-based) to explore and analyze data and interpret the results produced by that software in context.
Use the results of the central limit theorems for sample proportions and sample means to predict the long-term patterns of variation of those statistics under repeated sampling based on an understanding of the normal distribution.

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