Students on

**Summer 2019, Fall 2019, or Spring 2020**requirements.
Students on **Summer 2019, Fall 2019, or Spring 2020** requirements.

The specialization requires at least 9 credit hours, including the requirements listed below.

**Media Research.**Two (2) courses from the .- P: A grade of C- or higher in MSCH-C 213; or consent of instructor. Examination of the effects of the mass media on human cognitions, attitudes, and behaviors, relying on empirical social science research; emphasis on the effects on individuals, although study will include groups, organizations, and social norms. Credit given for only one of MSCH-S 315 or TEL-T 314. (3 credit hours.)
- P: A grade of C- or higher in MSCH-C 207; or consent of instructor. The behavior, descriptors, and measurement of telecommunications audiences. Sample survey, focus groups, and other research methods used by the telecommunications industry. Credit given for only one of MSCH-S 348 or TEL-T 348. (3 credit hours.)
- P: A grade of C- or higher in MSCH-C 101 or MSCH-H 101. Basic media theories as well as cognitive, emotional, and social psychology, with a focus on how these theories can be applied to the design of media messages. Special attention given to interactive and immersive mediated environments. Credit given for only one of MSCH-S 471 or TEL-T 471. (3 credit hours.)
- P: Application approved by director of undergraduate studies and instructor. Application is available on the Media School website. Opportunity for independent readings, research, and experimentation on relevant issues in media and communications; work with faculty member on individual basis. May be repeated for a maximum of 6 credit hours in JOUR-J 499, MSCH-J 499, and MSCH-X 498. (1–4 credit hours.)

**Statistics.**One (1) course from the .- R: To be successful in this course, students should have an understanding of basic algebra.. CJUS-K 300 covers the properties of single variables, the measurement of association between pairs of variables, and statistical inference. Additional topics, such as the analyses of qualitative and aggregated data, address specific criminal justice concerns. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370, ECON-S 370, MATH-K 300, MATH-K 310, POLS-Y 395, PSY-K 300, PSY-K 310, SOC-S 371, STAT-K 310, STAT-S 300, STAT-S 301, or SPEA-K 300. (3 credit hours.)
- P: ECON-E 201 or ECON-S 201; and MATH-M 118 or consent of instructor. R: ECON-E 202 or ECON-S 202 and MATH-M 119. Lectures emphasize the use of basic probability concepts and statistical theory in the estimation and testing of single parameter and multivariate relationships. In computer labs, using Microsoft Excel, each student calculates descriptive statistics, probabilities, and least squares regression coefficients in situations based on current business and economic events. Credit given for only one of ECON-E 370 or ECON-S 370; ANTH-A 306; CJUS-K 300; MATH-K 300 or MATH-K 310; POLS-Y 395; PSY-K 300 or PSY-K 310; SOC-S 371; STAT-K 310 or STAT-S 300, STAT-S 301, or STAT-S 303; or SPEA-K 300. (3 credit hours.)
- P: Admission to the LAMP honors certificate program. A discussion course emphasizing the use of quantitative methods and analytical skills in exploring and solving business-related problems. Topics vary with the instructor and year and include mathematical modeling and operations research, organizational control, and corporate finance. (3 credit hours.)
- P: One of MATH-M 106, MATH-M 118, MATH-M 119, MATH-M 211, MATH-M 212, MATH-S 211, MATH-S 212, MATH-V 118, or, MATH-V 119. Introduction to statistics; nature of statistical data; ordering and manipulation of data; measures of central tendency and dispersion; elementary probability. Concepts of statistical inference and decision: estimation and hypothesis testing. Special topics include regression and correlation, analysis of variance, non-parametric methods. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370 or ECON-S 370, MATH-K 300 or MATH-K 310, POLS-Y 395, PSY-K 300 or PSY-K 310, SOC-S 371, SPEA-K 300, or STAT-K 310, STAT-S 300, or STAT-S 301. (3 credit hours.)
- P: One of MATH-M 106, MATH-M 118, MATH-M 119, MATH-M 211, MATH-M 212, MATH-S 211, MATH-S 212, MATH-V 118, or, MATH-V 119. Introduction to probability and statistics; elementary probability theory, conditional probability, independence, random variables, discrete and continuous probability distributions, measures of central tendency and dispersion. Covers concepts of statistical inference and decision; estimation and hypothesis testing; Bayesian inference; and statistical decision theory. Special topics include regression and correlation, time series, analysis of variance, non-parametric methods. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370 or ECON-S 370, MATH-K 300 or MATH-K 310, POLS-Y 395, PSY-K 300 or PSY-K 310, SOC-S 371, SPEA-K 300, or STAT-K 310, STAT-S 300, or STAT-S 301. (3 credit hours.)
- Introduces the logic of statistical inference. Students will learn how to use sample data to reach conclusions about a population of interest by calculating confidence intervals and significance tests. Estimating the effects of multiple independent variables using cross-tabulations and/or regression. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370 or ECON-S 370, MATH-K 300 or MATH-K 310, POLS-Y 395, PSY-K 300 or PSY-K 310, STAT-K 310 or STAT-S 300 or STAT-S 301, SOC-S 371, or SPEA-K 300. (3 credit hours.)
- R: Mastery of high school algebra; or MATH-M 014. Essential statistical concepts and tools for journalists in the age of data, including probability, graphics, descriptive statistics, prediction, study design, comparison, testing, and estimation. The course has a heavier emphasis on writing and reading media reports than other introductory statistics courses. (3 credit hours.)
- R: Mastery of high school algebra; or MATH-M 014. Lecture and laboratory. Introduction to methods for analyzing quantitative data. Graphical and numerical descriptions of data, probability models of data, inference about populations from random samples. Regression and analysis of variance. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370 or ECON-S 370, MATH-K 300 or MATH-K 310, POLS-Y 395, PSY-K 300 or PSY-K310, SOC-S 371, SPEA-K 300, or STAT-K 310, STAT-S 300 or STAT-S 301. (4 credit hours.)
- R: Mastery of high school algebra; or MATH-M 014. Introduction to methods for analyzing data arising in the life sciences, designed for biology, human biology, and pre-medical students. Graphical and numerical descriptions of data, probability models, fundamental principles of estimation and hypothesis testing, inferences about means, correlation, linear regression. Credit given for only one of ANTH-A 306, CJUS-K 300, ECON-E 370 or ECON-S 370, MATH-K 300 or MATH-K 310, POLS-Y 395, PSY-K 300 or PSY-K310, SOC-S 371, SPEA-K 300, or STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303. (3 credit hours.)

**GPA, Minimum Grade, and Other Requirements.**Each of the following:- Except for the GPA requirement, a grade of C- or higher is required for a course to count toward a requirement in the specialization.
- A GPA of at least 2.000 for all courses taken in the specialization—including those where a grade lower than C- is earned—is required.
- Exceptions to specialization requirements may be made with the approval of the department's Director of Undergraduate Studies, subject to final approval by the College of Arts and Sciences.

Office of Undergraduate Curriculum, Policy + Records

Undergraduate Academic Affairs

The College of **Arts + Sciences**