The Media School

# Specialization in Media Research (Bachelor of Arts in Media)

Students on Summer 2021, Fall 2021, or Spring 2022 requirements MDAS23

## Requirements

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

**Media Research.**Two (2) courses:- MSCH-S 315 Media Processes and Effects
- MSCH-S 348 Audience Analysis
- MSCH-S 471 Applying Theory to Media Design
- MSCH-X 498 Research in Media

# MSCH-S 315 Media Processes and Effects

- Credits
- 3
- Prerequisites
- A grade of C- or higher in MSCH-C 213; or consent of instructor
- Description
- 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.
- Repeatability
- Credit given for only one of MSCH-S 315 or TEL-T 314.

- Fall 2024CASE SHcourseSummer 2024CASE SHcourse

# MSCH-S 348 Audience Analysis

- Credits
- 3
- Prerequisites
- None
- Description
- The behavior, descriptors, and measurement of telecommunications audiences. Sample survey, focus groups, and other research methods used by the telecommunications industry.

- Fall 2024CASE SHcourseSummer 2024CASE SHcourse

# MSCH-S 471 Applying Theory to Media Design

- Credits
- 3
- Prerequisites
- A grade of C- or higher in MSCH-C 101 or MSCH-H 101
- Description
- 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.
- Repeatability
- Credit given for only one of MSCH-S 471 or TEL-T 471.

# MSCH-X 498 Research in Media

- Credits
- 1–4 credit hours
- Prerequisites
- Application approved by director of undergraduate studies and instructor
- Notes
- Application is available on the Media School website
- Description
- Opportunity for independent readings, research, and experimentation on relevant issues in media and communications; work with faculty member on individual basis.
- Repeatability
- May be repeated for a maximum of 6 credit hours in JOUR-J 499, MSCH-J 499, and MSCH-X 498.

**Statistics.**One (1) course:- CJUS-K 300 Techniques of Data Analysis
- ECON-E 370 Statistical Analysis for Business and Economics
- LAMP-L 316 Junior Seminar: Analytical Problem Solving
- PSY-K 300 Statistical Techniques
- PSY-K 310 Statistical Techniques
- SOC-S 371 Statistics in Sociology
- STAT-S 211 Statistics for Journalists
- STAT-S 300 Introduction to Applied Statistical Methods
- STAT-S 303 Applied Statistical Methods for the Life Sciences

# CJUS-K 300 Techniques of Data Analysis

- Credits
- 3
- Prerequisites
- None
- Notes
- R: To be successful in this course, students should have an understanding of basic algebra.
- Description
- 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.
- Repeatability
- 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, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# ECON-E 370 Statistical Analysis for Business and Economics

- Credits
- 3
- Prerequisites
- MATH-M 118, MATH-S 118, or MATH-V 118
- Notes
- R: ECON-E 252 or ECON-B 252 and MATH-M 119
- Description
- 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.
- Repeatability
- 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, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# LAMP-L 316 Junior Seminar: Analytical Problem Solving

- Credits
- 3
- Prerequisites
- Admission to the LAMP honors certificate program
- Description
- 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.

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# PSY-K 300 Statistical Techniques

- Credits
- 3
- Prerequisites
- 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
- Description
- 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.
- Repeatability
- 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, SPEA-K 300, SPH-Q 381, STAT-K 310, STAT-S 300, STAT-S 301, or STAT-S 303.

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# PSY-K 310 Statistical Techniques

- Credits
- 3
- Prerequisites
- 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
- Description
- 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.
- Repeatability

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# SOC-S 371 Statistics in Sociology

- Credits
- 3
- Prerequisites
- None
- Description
- 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.
- Repeatability

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# STAT-S 211 Statistics for Journalists

- Credits
- 3
- Prerequisites
- None
- Notes
- R: Mastery of high school algebra; or MATH-M 014
- Description
- 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.

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# STAT-S 300 Introduction to Applied Statistical Methods

- Credits
- 4
- Prerequisites
- None
- Notes
- R: Mastery of high school algebra; or MATH-M 014. Lecture and laboratory
- Description
- 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.
- Repeatability

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

# STAT-S 303 Applied Statistical Methods for the Life Sciences

- Credits
- 3
- Prerequisites
- None
- Notes
- R: Mastery of high school algebra; or MATH-M 014
- Description
- 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.
- Repeatability

- Fall 2024CASE NMcourseSummer 2024CASE NMcourse

**Specialization GPA, Hours, and Minimum Grade Requirements.****Minimum Grade.**Except for the GPA requirement, a grade of C- or higher is required for a course to count toward a requirement in the specialization.**Minor GPA.**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.

##### Specialization Area Courses

Unless otherwise noted below, the following courses are considered in the academic program and will count toward academic program requirements as appropriate:

- Any course contained on the course lists for the academic program requirements at the time the course is taken—as well as any other courses that are deemed functionally equivalent—except for those listed only under Addenda Requirements
- Any course directed to a non-Addenda requirement through an approved exception

Exceptions to and substitutions for specialization requirements may be made with the approval of the unit's Director of Undergraduate Studies, subject to final approval by the College of Arts and Sciences.