Statistics   Department Information   Program Description   Career Opportunities   Preparation   Honors in Statistics   Major Requirements (B.S.)   Other Degree Requirements   Minor Requirements   Undergraduate Courses
Department Information	Department of Statistics and Biostatistics College of Science Office: North Science 229 Phone: (510) 885-3435   Professors Emeriti Michael L. Orkin, Ph.D. University of California, Berkeley Bruce E. Trumbo, Ph.D. University of Chicago   Professor Julia A. Norton Ph.D. Harvard University   Associate Professor Eric A. Suess (Chair), Ph.D. University of California, Davis   Assistant Professors Lynn Eudey, Ph.D. University of California, Berkeley Shenghua (Kelly) Fan, Ph.D. University of Minnesota Joshua D. Kerr, Ph.D. University of California, Davis Jaimyoung Kwon, Ph.D. University of California, Berkeley Mitchell R. Watnik, Ph.D. University of California, Davis YanYan Zhou, Ph.D. University of Maryland   Lecturers Ward A. Rodriguez, Ph.D. University of New Mexico Clyde N. Sugahara, Ph.D. University of California, Berkeley     Please consult the 2009-2010 online catalog for any changes that may occur.
Program Description	Statistics is the study of designing experiments and surveys, and evaluating the data obtained from them in a mathematical way. This rapidly growing science is widely used to make predictions about future events based on patterns observed in the past and to draw accurate inferences about large groups on the basis of a representative sample from the group. Economic forecasts and public opinion polls are examples of these kinds of statistical methods.   The methodology of statistics can be adapted to a wide spectrum of problems. Due to the extensive development of computers and the collection of large data banks, the need for statistical techniques has mushroomed in the past few decades. A society like ours, which has become increasingly dependent on its data, has a growing need for statisticians.   Student Learning Outcomes Students graduating with a B.S. in Statistics from Cal State East Bay will have:   1.  interpretive and basic computational skill in descriptive statistics and graphical displays; hypothesis testing and confidence intervals; modeling and error analysis;   2.  the ability to communicate to others results involving descriptive statistics and graphical displays; hypothesis testing and confidence intervals; modeling and error analysis;   3.  the ability to use appropriate statistical computer software and to decipher standard computer results covering descriptive statistics and graphical displays; hypothesis testing and confidence intervals; modeling and error analysis.
Career Opportunities	Actuary • Biostatistician • Business Executive • Census Analyst • Credit Analyst • Data Analyst • Economist • Financial Modeling Specialist • Forms Analyst • Information Systems Analyst • Insurance Agent • Market Researcher • Oddsmaker • Quality Control Specialist • Research Statistician • Sales Analyst • SAS Programmer • Statistician • Survey Designer • Systems Analyst • Teacher
Preparation	For Advanced Placement course equivalencies, see the Registration chapter.   The theory of statistics rests on a mathematical foundation. Even for statisticians whose primary interest is in applications, challenging mathematical problems arise continually. Calculus and computer programming are required for the major. An elementary course in linear algebra is highly recommended.   Courses in areas to which statistics is applied will also be helpful. Examples are business, biology, chemistry, geography, social sciences, psychology, and physics.   Community college students are advised to complete the sequence of elementary calculus and analytic geometry courses before transferring to Cal State East Bay. Another excellent lower-division requirement to complete before transferring is a course in introductory computer programming.
Honors in Statistics	Students earning a GPA of 3.6 or higher in courses comprising their major in Statistics will be awarded Honors in the degree provided the coursework applied toward the degree includes the courses listed in areas I and II below.   I.  Required Courses for Honors (16 units) MATH 2101 Elements of Linear Algebra (4) MATH 2304 Calculus III (4) MATH 3100 Linear Algebra (4) or MATH 3300 Analysis I (4) STAT 3402 Introduction to Probability Theory II (4)   II.  Required Honors Course (4 units) STAT 4401 Introduction to Stochastic Processes (4) or STAT 4601 Regression (4) taken as a special honors course with permission of the instructor and the Director of the Honors Program.
Major Requirements (B.S.)	Please consult an advisor in your major department for clarification and interpretation of your major requirements. The major consists of 68 units; the B.S. degree requires a total of 180 units.   I.  Basic Requirements (16-26 units) MATH 1304, 1305 Calculus I, II (4, 4) [prerequisite: MATH 1300 (4) or equivalent]   One of the following (4 units): CS 1020 Introduction to Computers (4) or CS 1160 Introduction to Computer Science and Programming Methods (4)   One of the following (4-10 units including prerequisite course): STAT 3010 Statistical Methods in the Social Sciences (4) [prerequisite, STAT 1000 (5)] or STAT 3031 Statistical Methods in Biology (4) or MGMT 3100 Decision Science (4) [prerequisite, STAT 2010 (5)] or MATH 2101 Elements of Linear Algebra (4) or MATH 2304 Calculus III (4)   II.  Mathematical Statistics and Probability (32 units) STAT/MATH 3401 Introduction to Probability Theory I (4) STAT/MATH 3502, 3503 Statistical Inference I, II (4, 4) STAT 3900 Data Analysis Using Statistical Packages (4) or 4950 Advanced Statistical Packages for Data Analysis (4) STAT 4601 Regression (4)   Any 3 of the following courses (12 units): STAT 3402 Introduction to Probability Theory II (4), 3510 Sampling Procedures for Surveys (4), 3910 Statistical Software Usage (4) or 4910 Advanced Statistical Package Usage (4), STAT/MATH 4401 Introduction to Stochastic Processes (4); STAT 4515 Applied Multivariate Analysis (4), 4610 Introduction to Nonparametric Statistical Methods (4)   III.  Area of Emphasis (20 units) Complete one of the following:   1.  Twenty units of approved mathematics or statistics courses in addition to those used for the requirements in Sections I and II. MATH 3100, Linear Algebra, or MATH 3300, Intermediate Analysis, should normally be included in these 20 units. These courses are especially recommended for students taking the mathematical statistics pattern, or wishing to apply to the master's degree program in Statistics. MATH 3100 or 3300 is required for students in the departmental honors program.   2.  Twenty units of approved courses in an approved area. Areas currently approved include the following: Anthropology, Biological Science, Business/Economics, Chemistry, Computer Science, Geography, Geological Sciences, History, Physics, Political Science, Psychology, Sociology. For a complete list of currently approved areas, contact the Department of Statistics.   To gain departmental approval, these courses must include at least one upper division course and be judged to constitute a coherent program of study. (With the approval of the department, upper division Statistics courses, except STAT 3001, 3010, and 3031, may be applied toward these twenty units.)   Credit/No Credit Courses It is the policy of the department that no course taken on a "CR/NC" basis may be applied toward any of the requirements of Section II above. Individual petitions for waiver of this policy will be treated according to the same procedures as petitions to waive other degree requirements.   Double Major A knowledge of statistical methods is of increasing importance to students in many areas, especially the physical, computing, decision, environmental, biological, political, and social sciences and administrative studies (including business, health care, and education). A second major in statistics along with a major in one of these areas may result in better preparation for employment or graduate study. The following three factors combine to make such a double major feasible in many cases:   1.  The Statistics major allows for a relatively large number of completely unrestricted elective units. The student may elect courses required for the other major among these.   2.  Up to twenty units in certain areas outside of Statistics may be applied toward the Statistics degree. (See Area of Emphasis requirement, III.2.)   3.  Some other majors require Statistics courses that also count towards the Statistics major (e.g., STAT 2010, 3010, 3031, 3401, 3502, etc.).   To obtain an illustrative program contact the Statistics Department.   Note: If a student simultaneously completes requirements for two majors leading toward different degrees (e.g., B.S. major in Statistics and B.A. major in Sociology), only one degree (student's choice) is awarded. However, in all cases, the student's transcript carries a notation that both sets of major requirements have been met. Students are eligible for scholarships in both programs.
Other Degree Requirements	In addition to major requirements, every student must also complete the University requirements for graduation which are described in the Baccalaureate Degree Requirements chapter in the front of this catalog. These include the General Education-Breadth requirements; the second composition (ENGL 1002) requirement; the cultural groups/women requirement; the performing arts/activities requirement; the U.S. history, U.S. Constitution, and California state and local government requirement; the University Writing Skills Requirement; and the residence, unit, and grade point average requirements.
Minor Requirements	Minor in Statistics The minor consists of 24-25 units; six courses not involving calculus prerequisites approved for all students in the minor are as follows:   One of the following courses: STAT 1000 Elements of Probability and Statistics (5), 2010 Elements of Statistics for Business and Economics (5), 3031 Statistical Methods in Biology (4)   Five of the following: STAT 3010 Statistical Methods in the Social Sciences (4), 3040 Probability, Risk and Chance (4), 3050 Statistics: from Data to Decisions (4), 3415 Introduction to Decision Theory (4), 3510 Sampling Procedures for Surveys (4), 3900 Data Analysis Using Statistical Packages (4), 3910 Statistical Software Usage (4), 4000 Analysis of Variance in the Behavioral Sciences (4), 4515 Applied Multivariate Analysis (4), 4601 Regression (4), 4610 Introduction to Nonparametric Statistical Methods (4)   With the consent of a Statistics Department advisor, any upper division Statistics course with a calculus prerequisite may be substituted for any of the above courses.     Minor in Biostatistics The minor consists of 24 units. Note that some courses require prerequisites not required in the minor.   Required Courses (16 units) STAT 3031 (4) and 4000 (4) or STAT/MATH 3502 and 3503 (8) (second sequence is preferred; however, it requires calculus.) STAT 4601 (4) STAT 4950 (4)   Elective courses (8 units) Two upper division courses in statistics not included in required coursework.
Undergraduate Courses	The course prefix for the following courses is STAT.   Information about Elementary Statistics Courses Prerequisite: All introductory statistics courses require as a prerequisite completion of the Entry Level Math (ELM) requirement.   First Statistics Course: The courses STAT 1000/3010 form a sequence and so STAT 1000 is the appropriate first course in many cases. Biology majors should take STAT 3031 as their first Statistics course. Business and Economics majors should take STAT 2010. Sociology majors who elect to take only one Statistics course should take STAT 1000. STAT 3401, STAT 3502, and STAT 3601 may be taken with no previous background in Statistics and are open to students with the appropriate Mathematics prerequisites.   Prohibitions: Students will NOT receive credit toward graduation for both STAT 1000 and 2010. STAT 1000 may not follow any upper division Statistics course. Business and Economics majors require STAT 2010 or STAT 3502 and so must not take STAT 1000 (unless substitution of 1000/3010 for 2010 or 3502 has been approved by the major department).   Substitutions: Some departments permit students with appropriate background or interests to substitute a more advanced course or pair of courses for a course(s) specified as required in the Catalog. Get advance written permission from your department before making any of the following substitutions: 2010 for 1000; 1000/3010 for 2010; 3401/3502 for 3601; 3502 for 3031; 3502 (plus 5 elective units) for 1000/3010; 3503 for 4000.   1000     Elements of Probability and Statistics (5) Descriptive statistics (measures of central tendency, dispersion, correlation), elementary discrete probability distributions. Introduction to tests of statistical hypotheses. Prerequisite: completion of ELM requirement. Not open to students with credit for STAT 2010.   2010     Elements of Statistics for Business and Economics (5) Introduction to modern probability, descriptive statistics, estimation, hypothesis testing, and linear regression. Applications to business and economics. Prerequisite: completion of ELM requirement. Not open to students with credit for STAT 1000.   2011     Introductory Regression for Business and Economics (1) Regression, including derivation and introduction to multiple regression. Computer aided computation, assumptions, and error analysis emphasized. Applications to business and economics. Prerequisite: STAT 1000 or equivalent, or MATH 1820.   3010     Statistical Methods in the Social Sciences (4) Standard scores, t scores, ranked data, linear regression, correlation, measures of association, the normal distribution and its uses, paired comparisons, the uses of chi-squared, and introduction to design of experiments. Prerequisite: STAT 1000 or equivalent.   3031     Statistical Methods in Biology (4) Basic probability and statistical concepts. Introduction to the analysis of variance, correlation, and simple linear regression. Nonparametric techniques with application to biology. Prerequisite: MATH 1130 or consent of instructor.   3040     Probability, Risk, and Chance (4) Basic ideas of probability. Dealing with misconceptions about chance phenomena and risk. Rules for finding probabilities, discrete random variables and their distributions, normal distribution. Examples from games of chance, physical, biological, and social sciences. Illustrations using computer simulation. Projects with written reports. Not for statistics B.S. degree credit. Acceptable for credit in the statistics minor. Prerequisite: lower division quantitative reasoning (GE Area B4) satisfied.   3050     Statistics: from Data to Decisions (4) Fundamentals of statistical reasoning illustrated with real data from such fields as biology, psychology, geology, anthropology, physics, medical technology. How to decide on an appropriate statistical method. Graphical methods, computer assisted analysis of data. Drawing conclusions. Projects with written reports. Not for statistics B.S. degree credit. Acceptable for credit in the statistics minor. Prerequisite: STAT 1000 or equivalent.   3088     Gambling and Games of Chance (4) A survey of popular gambling games, including dice games, card games, and horse racing. Discussion of odds and probabilities, and how to turn those into gambling strategies. Not for statistics B.S. degree credit. Prerequisite: lower division quantitative reasoning, General Education Area B4, satisfied.   3401     Introduction to Probability Theory I (4) The theory of probability with applications to science and engineering. Sample spaces; random variables; joint, marginal, conditional distributions; expectations; important distributions (binomial, Poisson, normal, etc.); and moment generating functions. Cross-listed with MATH 3401. Prerequisite or concurrent: MATH 1305.   3402     Introduction to Probability Theory II (4) Generating functions and multivariate distributions. Conditioning. Chebyshev inequality and limit theorems. Multidimensional transformations of random variables. Derivation of t and F distributions. Uses of probability theory in mathematical statistics. Cross-listed with MATH 3402. Prerequisite: STAT/MATH 3401 or STAT/MATH 4412.   3502     Statistical Inference I (4) Random variables, sampling distributions (binomial, Poisson, normal, exponential), conditional probability. Estimation, hypothesis testing. Computer-aided computations. Topics include: t-tests, correlation, regression; proportions, chi-squared; ANOVA. Cross-listed with MATH 3502. Prerequisite: MATH 1305 or MATH 1820.   3503     Statistical Inference II (4) General linear hypothesis with emphasis on design and analysis of experiments. Data from science, engineering, and quality management. Factorial designs: random effects, nesting. Optional topics: incomplete blocks, missing data, analysis of covariance. Computer-aided analysis. Cross-listed with MATH 3503. Prerequisite: STAT 3502 or 3601.   3510     Sampling Procedures for Surveys (4) Detailed investigation of sampling methods. Design and comparisons of stratified, systematic, and cluster sampling procedures. Techniques of multistage and multiphase sampling. Prerequisite: STAT 1000 or equivalent.   3601     Statistics and Probability for Science and Engineering I (4) Basic probability rules (independence, Bayes' Theorem), distributions (binomial, Poisson, normal, exponential), reliability. Descriptive, inferential statistics (control charts, estimation, hypothesis testing: one, two samples), correlation, regression. Emphasizes: computer analysis, simulation; science, engineering applications. Not open to those with credit for STAT/ENGR/MATH 3502. Cross-listed with ENGR 3601. Prerequisite: MATH 1305.   3602     Statistics and Probability for Science and Engineering II (4) General linear model with emphasis on design and analysis of experiments. Fixed and random effects and nested models. Power and sample size considerations. Emphasizes: computer analysis, simulation; science, engineering applications. Not open to those with credit for STAT/ENGR/MATH 3503. Cross-listed with ENGR 3602. Prerequisite: STAT/ENGR/MATH 3502 or STAT/ENGR 3601.   3898     Cooperative Education (1-4) Supervised work experience in which student completes academic assignments integrated with off-campus paid or volunteer activities. May be repeated for up to 4 units. A maximum of 4 units will be accepted toward the Statistics major. Prerequisites: at least 2.0 GPA; departmental approval of activity.   3900     Data Analysis Using Statistical Packages (4) Using computer packages (e.g., SPSS, SAS) and interpreting output. Data preparation, descriptive statistics, graphs, checks for normality, t-tests, F-tests, ANOVA, cross tabulations, chi-squared tests, correlation, and report preparation. Prerequisite: a previous course in statistics.   3910     Statistical Software Usage (4) Using program code in a statistical software package (e.g., SPSS, R or SAS), producing reformatted data and statistical analysis. Topics may include graphics, creating and managing data files, and simulations. Prerequisites: a previous Statistics course and skill in computer usage.   3999     Issues in Statistics (4) Readings, discussion, and research on contemporary and/or significant issues in statistics. May be repeated for credit when content varies.   4000     Analysis of Variance in the Behavioral Sciences (4) Review of elementary analysis of variance. Factorial analysis of variance, multiple comparisons, and repeated measures designs. Prerequisite: STAT 3010 or STAT 3031.   4013     Statistics, Data Analysis, and Probability (4) (See MATH 4013 for course description.)   4401     Introduction to Stochastic Processes (4) Theory of stochastic models with applications to science and engineering. Markov processes. Elementary birth-death processes, queues. Limit theorems. Computer simulation. Applications: e.g., inventory models, reliability, epidemiology. Cross-listed with MATH 4401. Prerequisite: STAT/MATH 3401 or STAT/ENGR 3601.   4412     Probability Theory (4) Same spaces; random variables, joint, marginal, conditional distributions; expectations for modeling data; related use of computer packages; moment generating functions; transforming a random variable. Not open to those with credit for STAT/MATH 3401. Cross-listed with MATH 4412. Prerequisite: MATH 1305.   4515     Applied Multivariate Analysis (4) MANOVA, repeated measures designs, discriminant functions. May include factor analysis, canonical correlation, and cluster analysis. Computer intensive with special emphasis on treatment of actual data. Written reports required. Prerequisites: STAT 3010 and 3900 (may be concurrent).   4601     Regression (4) Computational methods in regression, including variable construction, and ANOVA. Selection methods. Attention to model assessment, graphical techniques, and assumption checking. Emphasis on real data from science, engineering, and business. Computer-assisted analysis. Report writing. Prerequisite or concurrent: STAT 3503 or STAT 4000.   4603     Operations Research II (4) Theory of stochastic models with applications to engineering. Markov processes, queues, birth-death processes. Operations research applications. Inventory models, risk theory, fatigue failure, and reliability. Computer simulation. Not open to those with credit for STAT/ENGR 3603 or STAT/ENGR/MATH 4401. Cross-listed with ENGR 4603. Prerequisite: STAT/ENGR 3602.   4610     Introduction to Nonparametric Statistical Methods (4) Nonparametric methods and distribution-free tests. Sign, Wilcoxon, rank-correlation, independence and randomness tests. Approximate distributions under the null hypothesis, treatment of ties, some estimation procedures. Emphasis on social science data. Prerequisite: STAT 3010.   4612     Statistical Inference in Practice (4) Probability ideas essential to statistical inference. Estimation and hypothesis-testing for univariate and bivariate data. Individual projects involving computer-aided analysis of real data. Prerequisites: senior or graduate standing, an upper-division STAT course, and MATH 2304.   4860-   4869     Undergraduate Seminar (4 each) Seminar in probability and/or statistics on topics extending beyond regular courses. Variable content, units, and prerequisites specified at the time of offering. A total of up to 12 units of different topics may be taken for credit.   4910     Advanced Statistical Package Usage (4) Programming in an advanced statistical software package, producing reformatted data, advanced statistical analysis, and probability modeling. Topics may include graphics, spatial statistics, creating and managing data files, simulations, approximation algorithms. Prerequisites: STAT 3502, CS 1160.   4950     Advanced Statistical Packages for Data Analysis (4) Programming and applying computer packages (e.g., SAS, S+). Data preparation and transformation, macros, descriptive statistics. Topics from diagnostics, t-procedures, ANOVA; nonparametrics; cross-tabulation, chi-squared, correlation, regression. Report writing. Cross-listed with ECON 4950. Prerequisite: STAT 3502.   4900     Independent Study (1-4)
Footnotes	These courses are especially recommended for students taking the mathematical statistics pattern.     May require additional prerequisites. May be taken if prerequisites are met.     Refer to "Information about Elementary Statistics Courses" section at the beginning of "Undergraduate Courses."
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