MATH 256 - Statistics for Business and Social Science
Study of descriptive and inferential statistics; boxplots, histograms and scatterplots; introduction to design of experiments; measures of central tendency; frequency distributions; probability distributions; sampling and sampling distributions; hypothesis testing; confidence intervals; and linear regression.
Prerequisite: MATH 106, MATH& 141 or MATH 147 with a grade of 2.0 or higher; or appropriate math placement. Recommended: Eligible for READ 104 .
Satisfies Requirement: Natural Science and Quantitative Skills
Students who successfully complete this class will be able to:
- Define and use common statistical terminology.
- Identify the major categories of experimental designs and sampling methods.
- Identify common sources of bias in surveys and experiments.
- Construct and interpret frequency distributions, histograms, pie charts, and box plots.
- Calculate and interpret the measures of center and spread.
- Carry out a linear regression analysis of paired data.
- State and apply the basic axioms and theorems of probability.
- State and apply the central limit theorem.
- Calculate confidence intervals and conduct hypothesis tests for one and two samples using the standard normal, Student-t, and Chi square distributions.
Recognize which quantitative or symbolic reasoning methods are appropriate for solving a given problem.
Correctly implement the quantitative or symbolic reasoning methods that are appropriate for solving a given problem.
Translate data into various formats such as symbolic language, equations, graphs, and formulas.
- Quantitative and Symbolic Reasoning - Quantitative Reasoning encompasses abilities necessary for a student to become literate in today’s technological world. Quantitative reasoning begins with basic skills and extends to problem solving.
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