# The Minor in Applied Statistics

## Course Requirements for the Minor: 18 units

The following courses, or their approved transfer equivalents, are required of all candidates for this minor.

#### Lower-Division Courses: 3 units

1 course selected from:

SUBJ NUM Title Sustainable Units Semester Offered Course Flags
Summary of numerical data, distributions, linear regression, and introduction to statistical inference. Statistical software is used. 1.5 hours lecture, 1.5 hours discussion. This is an approved General Education course. (005501)
Descriptive statistics, sampling theory, statistical inference and tests of hypotheses, analysis of variance, chi-square tests, simple regression and correlation, and multiple regression and correlation. 1.5 hours lecture, 1.5 hours discussion. This is an approved General Education course. (001042)

#### Upper-Division Courses: 9 units

3 courses required:

SUBJ NUM Title Sustainable Units Semester Offered Course Flags
Prerequisite: MATH 105, MATH 109, or MATH 120, or faculty permission.
Single and two sample inference, analysis of variance, multiple regression, analysis of co-variance, experimental design, repeated measures, nonparametric procedures, and categorical data analysis. Examples are drawn from biology and related disciplines. The statistical programming language R is used. Appropriate for biology, agriculture, nutrition, psychology, social science and other majors. 3 hours discussion. (005568)
Prerequisites: MATH 314 or MATH 315.
Advanced topics in applied statistics including multiple and logistic regression, multivariate methods, multi-level modeling, repeated measures, and others as appropriate. The statistical programming language R is used. Appropriate for biology, agriculture, nutrition, business, psychology, social science and other majors. 3 hours discussion. (005570)
Prerequisite: MATH 314, MATH 315, or MATH 351 (may be taken concurrently).
The theory and application of survey sampling techniques. Topics include simple random sampling, stratified sampling, systematic sampling, and cluster sampling. Appropriate for mathematics, computer science, psychology, social science, agriculture, biology, and other majors. 3 hours discussion. (005573)

#### Electives: 6 units

6 units selected from:

At least 6 units of electives must be chosen from either the Department of Mathematics and Statistics or from another department. Electives must be courses with significant mathematical/statistical content as determined by faculty of the Department of Mathematics and Statistics. Prior approval is required to count Independent Study or Internships towards the Minor. Acceptable courses include:

SUBJ NUM Title Sustainable Units Semester Offered Course Flags
A survey of selected mathematical and logical methods and models of relevance to various problems in anthropology. Emphasis is placed on the analysis of anthropological data. 3 hours seminar. (000530)
Prerequisites: ABUS 301, ECON 102.
Domestic and international issues in U.S. agricultural food policy. A study of the major problems confronting agriculture, the process by which government formulates agricultural policy, and the socio-economic impact of current government programs. 3 hours lecture. This is an approved Writing Course. (000029)
Prerequisites: BIOL 360.
A detailed study of the evolutionary process, including history, natural selection, population genetics, molecular evolution, speciation, coevolution, and macroevolution. 3 hours discussion. (001201)
Prerequisites: Classified MBA student.
An examination of applications and information system platforms designed to support and improve business decision making. Exposure to relevant quantitative methods and their potential business value, combined with hands-on use of current technology. Case studies requiring the development of clearly communicated recommendations supported by sound analysis. 3 hours seminar. (001081)
Prerequisites: GE Mathematics/Quantitative Reasoning Ready, CSCI 111 with a grade of C or higher (may be taken concurrently), MATH 119 (or equivalent).
This course is also offered as MATH 217.
Offers an intensive introduction to discrete mathematics as used in computer science. Topics include sets, relations, propositional and predicate logic, basic proof methods including mathematical induction, digital logic circuits, complexity of algorithms, elementary combinatorics, and solving linear recurrence relations. 3 hours discussion. (005550)
Prerequisites: CHEM 112 with a grade of C- or higher.
Precision and accuracy in measurements, interpretation of data by statistical analysis, and development of good quantitative techniques. Analysis by gravimetry, titrimetry, potentiometry, chromatography, and spectrometry. 2 hours discussion, 6 hours laboratory. (001847)
Prerequisites: CHEM 370M, MATH 220; PHYS 202A and PHYS 202B or PHYS 204A, PHYS 204B, and PHYS 204C.
Overview of fundamental principles of time-independent quantum mechanics and spectroscopy, statistical thermodynamics, and chemical kinetics. 3 hours discussion. (001882)
Prerequisites: ECON 102 or ECON 103, MATH 105 or faculty permission.
The objective of this course is to show the relevance of statistic analysis for economics. Each topic is presented with an application of a macroeconomic or microeconomic theory. Real data is used in software applications for developing a conceptual understanding of the problem and for analyzing the data. 3 hours discussion. (002675)
Prerequisites: ECON 301, ECON 302, ECON 380.
Use of mathematics and statistics to design and test econometric models. 3 hours discussion. (002699)
Prerequisites: ECON 380, ECON 481.
This course provides tools of applied econometric analysis by building upon the concepts of econometrics and regression analysis attained in Econ 481. The students will be working closely with data as well as statistical software and use applied econometric methods beyond the linear regression model. 3 hours seminar. (002701)
Prerequisites: GEOG 211, MATH 105 or equivalents.
Introduction to quantitative analysis of spatial data using single and two sample inference, analysis of variance, correlation, multiple regression, analysis of co-variance, experimental design, repeated measures, nonparametric procedures, categorical data analysis, clustering/classification, and principal components analysis. Examples are drawn from geographical themes in economics, demography, politics, planning, natural and earth sciences. Statistical packages are introduced. 3 hours lecture. (003881)
Prerequisites: GEOG 101W, GEOG 102, and GEOG 390W or equivalents. Recommended: GEOG 343, GEOG 444, GEOG 445, or PSSC 330.
An analysis of the complex interactions between humans, plants, and animals in the restoration process. Includes the use of maps and other graphic material as well as reading, lecture, and discussion. Emphasis on how human activities can affect the distribution and abundance of various plant and animal species in both negative and positive ways. Restoration work on the Butte Creek Ecological Reserves and other similar sites provide a focus for class projects and discussion. 3 hours lecture. Formerly GEOG 405S. (003930)
Prerequisites: GEOG 211, GEOG 313, GEOG 315 or equivalents.
Advanced geospatial analysis and modeling techniques using Geographic Information Systems (GIS). Topics include geoprocessing, Python programming, and geospatial modeling. Students collaborate to design, develop, and present a GIS pilot study. They apply GIS theory and techniques to solve problems in land and resource management, utilities, and municipal government. Covers all stages of a GIS project: planning, design, analysis, and presentation. 2 hours lecture, 1 hour activity. (003942)
Prerequisites: GEOG 211; GEOG 315 or MATH 105, or equivalents.
An introduction to the theory, techniques, data acquisition, processing, and presentation of imagery acquired through aerial photographic and satellite means of remote sensing. Application of basic skills of aerial photographic interpretation and satellite digital image processing and analysis to physical and cultural geographic phenomena. 3 hours lecture. (003941)
Prerequisites: GEOG 101W, GEOG 211, GEOG 343, GEOG 390W or equivalents. Recommended: BIOL 161, BIOL 350W, GEOG 315.
Biogeography and landscape ecology are keys for evaluating plant and animal distributions at local to global spatial scales. This course seeks to understand the physical and biological processes that determine these patterns through time, as well as help design management strategies for conserving our planet's biological diversity, and thus ecosystem services. The course emphasizes nature and impact of continuity and patchiness of species distributions and movement, and material flow on the structure and dynamics of wildland, agrarian, and urbanized landscapes. This is thus a highly integrative field of inquiry, pulling on concepts, theories and data from general ecology, evolutionary biology, geology, and physical and human geography. Quantitative methods and field trips consider the biogeography of plants and animals in the local landscapes. 2 hours lecture, 2 hours activity. (003929)
Prerequisite: PHYS 202B, PHYS 204B, or PHYS 204C (may be taken concurrently).
Instruments are critical to making quantitative observations, and observations are critical to the scientific method. The subject of environmental instrumentation is vast and constantly changing as new technologies emerge. Through a combination of lectures and hands-on projects, students are (1) introduced to the process of assembling and characterizing an electronic instrument of their own, (2) forming a hypothesis and testing it by collecting data, and (3) writing reports and giving presentations on their results. 2 hours lecture, 3 hours laboratory. (020639)
Prerequisites: GE Mathematics/Quantitative Reasoning Ready; MATH 118, MATH 119 (or high school equivalents).
This course covers the fundamental concepts and techniques of differential and integral calculus with an introduction to differential equations. Emphasis on applications from the Life Sciences. This course is not intended for majors in mathematics, physics, chemistry, or engineering. No credit for students with credit in MATH 120. A score that meets department guidelines on a department administered calculus readiness exam must be achieved by those who claim high school equivalence. 4 hours discussion. This is an approved General Education course. (005512)
Prerequisites: GE Mathematics/Quantitative Reasoning Ready, CSCI 111 with a grade of C or higher (may be taken concurrently), MATH 119 (or equivalent).
This course is also offered as CSCI 217.
Offers an intensive introduction to discrete mathematics as used in computer science. Topics include sets, relations, propositional and predicate logic, basic proof methods including mathematical induction, digital logic circuits, complexity of algorithms, elementary combinatorics, and solving linear recurrence relations. 3 hours discussion. (005550)
Prerequisites: MATH 121; and one of the following: CINS 110, CSCI 111, MATH 130 (may be taken concurrently), MATH 230 or MECH 208.
Basic concepts of probability and statistics with emphasis on models used in science and technology. Probability models for statistical estimation and hypothesis testing. Confidence limits. One- and two-sample inference, simple regression, one- and two-way analysis of variance. Credit cannot be received for both MATH 314 and MATH 315. 4 hours discussion. This course requires the use of a laptop computer and appropriate software. (005533)
Prerequisites: MATH 121.
Basic concepts of probability theory, random variables and their distributions, limit theorems, sampling theory, topics in statistical inference, regression, and correlation. 3 hours discussion. (005534)
Prerequisites: MATH 108, MKTG 305.
User-oriented analysis of the marketing research process, including problem definition, proposal preparation, research design, data collection, sampling methods, data analysis, interpretation, and presentation of findings. 3 hours lecture. (005876)
Prerequisites: ENGL 130W or JOUR 130W (or equivalent) with a grade of C- or higher, PSYC 101, PSYC 261.
The analysis of research data in psychology using inferential statistical methods, with an emphasis on relevant statistical designs, understanding statistical conclusions in published research, and professional report writing. Descriptive statistics, graphing, hypothesis testing, correlation and regression, chi-square, t-tests, and analysis of variance. Single factor designs and ANOVA, post-hoc comparisons, repeated measures ANOVA, and simple factorial designs. Professional reporting of research. Laboratory provides examples, applications, and development of research data analysis and statistical evaluation skills. 3 hours lecture, 3 hours laboratory. (007904)
Prerequisites: A course in statistics including research design.
Basic psychological measurement theory and principles of test construction. 2 hours discussion, 2 hours activity. (007960)
Prerequisites: SOCI 310. MATH 105 or other lower-division statistics course recommended.
This course studies descriptive and inferential statistics used for the social sciences. Emphasis is on the integration of statistical research designs and data, appropriate statistical analysis, interpretation of relevant findings, and visual presentation. 3 hours seminar. (008971)
Catalog Cycle:21