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    K-State Undergraduate Catalog 2000-2002
     

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    Statistics

    Dallas E. Johnson,* Head

    Professors Boyer,* Higgins,* Johnson,* Kemp,* Milliken,* Nelson,* and Yang;* Associate Professors El Barmi,* Loughin,* Neill,* Pontius* and Rumsey;* Assistant Professor Zhou;* Emeritus: Professors Perng, Feyerherm, and Fryer.

    785-532-6883
    Fax: 785-532-7736
    E-mail: head@stat.ksu.edu
    www.ksu.edu/stats/

    Statistics is a combination of classical mathematics, the theory of probability, and new concepts related to inductive reasoning that have developed during the past 75 years.

    Almost all activities of plants and animals (including people) depend to some degree on chance events, and most decisions made by people depend on sampling information—which also depends on chance events, and hence on probability. Consequently, fields of interest and activities for a statistician potentially are very broad.

    Likewise, the professional activities open to a trained statistician are quite varied. The existence of modern-day computers relieves the statistician of tedious computations and elevates his or her professional activity to dealing with people and/or engaging in basic research.

    Students who major in statistics may seek a bachelor of arts degree or a bachelor of science degree by satisfying the general requirements of that degree, and completing the following:

    MATH 220Analytic Geometry and Calculus I 4
    MATH 221Analytic Geometry and Calculus II 4
    MATH 222Analytic Geometry and Calculus III 4
    MATH 551Applied Matrix Theory 3
    CIS 200Fundamentals of Computer
    Programming 2
    CIS 203Fundamentals of Computer
    Programming Lab 1
    STAT 410Probabilistic Systems Modeling 3
    STAT 510Introductory Probability and
    Statistics I 3
    STAT 511Introductory Probability and
    Statistics II 3
    STAT 704Analysis of Variance and Covariance 2
    STAT 705Regression and Correlation Analyses 2
    STAT 720Design of Experiments 3
    IE 541Statistical Quality Control 3
    Statistics elective (STAT 710, 716, 717, or 722) 3
    ENGL 516Written Communication for the
    Sciences 3
     
    Upper division quantitative electives 9
    (May include mathematics, computer science, or other approved courses)
    A minimum of 2.0 GPA in STAT courses taken as part of the major is required for graduation.
     
    Statistics minor
    Students interested in quantitative methods to complement their major area of study may select a minor in statistics. The requirements are:

    One of: STAT 320, 330, 340, 350, 510
    One of: STAT 341, 351, 511
    Both: STAT 704, 705
    Five additional hours that require statistics as a prerequisite. Courses may be statistics courses or quantitative courses from another department.
     
    Dual majors and dual degrees
    Students may major in statistics and another discipline within the College of Arts and Sciences. The degree requirements of both departments must be met. For instance, it is possible to complete a dual statistics-mathematics degree in four years.

    Students may obtain a dual degree in statistics and a field in another college such as business administration or engineering. The degree requirements of both colleges must be met and a minimum of 150 hours must be completed. Students who choose this option should complete the calculus sequence by the end of the sophomore year.

    Statistics courses
    University General Education courseSTAT 100. Statistical Literacy in the Age of Information. (3) I, II. This course is intended for majors in non-quantitative fields. Focus will be on the development of an awareness of statistics at the conceptual and interpretative level, in the context of everyday life. Data awareness and quality, sampling, scientific investigation, decision making, and the study of relationships are included. Emphasis will be on the development of critical thinking through in-class experiments and activities, discussions, analyses of real data sets, written reports, and collaborative learning. Computing activities will be included where appropriate; no previous computing experience required. Pr.: MATH 100. Cannot be taken for credit if credit has been received for any other statistics course.

    University General Education courseSTAT 320. Elements of Statistics. (3) I, II, S. A basic first course in probability and statistics; frequency distributions; averages and measures of variation; probability; simple confidence intervals and tests of significance appropriate to binomial and normal populations; correlation and regression, including confidence intervals and tests of significance for bivariate populations. Pr.: MATH 100.

    University General Education courseSTAT 330. Elementary Statistics for the Social Sciences. (3) I, II, S. A basic first course in probability and statistics with textbook, examples, and problems aimed toward the social sciences and humanities. Frequency distributions, averages, measures of variation, probability, confidence intervals; tests of significance appropriate to binomial, multinomial, and normal sampling; simple regression and correlation. Pr.: MATH 100. Cannot be taken for credit if credit has been received for STAT 320, 340, or 350.

    University General Education courseSTAT 340. Biometrics I. (3) I, II. A basic first course in probability and statistics with textbook, examples, and problems aimed toward the biological sciences. Frequency distributions, averages, measures of variation, probability, confidence intervals; tests of significance appropriate to binomial, multinomial, Poisson, and normal sampling; simple regression and correlation. Pr.: MATH 100. Cannot be taken for credit if credit has been received for STAT 320, 330, or 350.

    STAT 341. Biometrics II. (3) II. Analysis and interpretation of biological data using analysis of variance, analysis of covariance, and multiple regression. Negative binomial distribution and its applications. Pr.: STAT 320, 330, 340, or 350.

    University General Education courseSTAT 350. Business and Economic Statistics I. (3) I, II, S. A basic first course in probability and statistics with textbook, examples, and problems pointed toward business administration and economics. Frequency distributions, averages, index numbers, time series, measures of variation, probability, confidence intervals, tests of significance appropriate to binomial, multinomial, Poisson, and normal sampling; simple regression and correlation. Pr.: MATH 100. Cannot be taken for credit if credit has been received for STAT 320, 330, or 340.

    STAT 351. Business and Economic Statistics II. (3) I, II, S. Continuation of STAT 350 including study of index numbers, time series, business cycles, seasonal variation, multiple regression and correlation, forecasting; some nonparametric methods applicable in business and economic studies. Pr.: STAT 320, 330, 340, or 350.

    University General Education courseSTAT 399. Honors Seminar in Statistics. (3) Selected topics. May be used to satisfy quantitative requirements for B.S. degree. Open only to students in the honors program.

    STAT 410. Probabilistic Systems Modeling. (3) II. Basic probability; discrete and continuous random variables; Markov chains; Poisson process; birth and death process; applications for queuing theory and reliability theory; computer simulation of random phenomena. Pr.: MATH 221, CIS 300, 570, or consent of instructor.

    STAT 490. Statistics for Engineers. (1) I, II. First course in statistics with examples and problems toward engineering. Distributions, means, measures of variation, confidence intervals, graphical display of data, simple regression and correlation, philosophy of experimentation. Must be taken conc. with a laboratory course in engineering which uses statistics.

    STAT 491. Statistics for Engineers II. (1) I, II. A continuation of STAT 490. Offered second half of the semester following STAT 490. Statistical tests, multiple regression, model fitting, simple comparative and factorial experiments. Emphasis on computer analysis of data. Pr.: STAT 490.

    STAT 510. Introductory Probability and Statistics I. (3) I, II. Descriptive statistics, probability concepts and laws, sample spaces; random variables; binomial, uniform, normal, and Poisson; two-dimensional variates; expected values; confidence intervals; binomial parameter, median, normal mean, and variance; testing simple hypotheses using CIs and X2 goodness of fit. Numerous applications. Pr.: MATH 222.

    STAT 511. Introductory Probability and Statistics II. (3) II. Law of Large Numbers, Chebycheff's Inequality; continuation of study of continuous variates; uniform, exponential, gamma, and beta distribution; Central Limit Theorem; distributions from normal sampling; introduction to statistical inference. Pr.: STAT 510.

    Undergraduate and graduate credit
    STAT 702. Statistical Methods for Social Sciences. (3) I, II. Statistical methods applied to experimental and survey data from social sciences; test of hypotheses concerning treatment means; linear regression; product-moment, rank, and bi-serial correlations; contingency tables and chi-square tests. Pr.: MATH 100.

    STAT 703. Statistical Methods for Natural Scientists. (3) I, II, S. Statistical concepts and methods basic to experimental research in the natural sciences; hypothetical populations; estimation of parameters; confidence intervals; parametric and nonparametric tests of hypotheses; linear regression; correlation; one-way analysis of variance; t-test; chi-square test. Pr.: Junior standing and equiv. of college algebra.

    STAT 704. Analysis of Variance. (2) I, II, S. Computation and interpretation for two- and three-way analyses of variance; multiple comparisons; applications including use of computers. Meets four times a week during first half of semester. Pr.: One previous statistics course.

    STAT 705. Regression and Correlation Analyses. (2) I, II, S. Multiple regression and correlation concepts and methods; curvilinear regression; applications including use of computers. Meets four times a week during second half of semester. Pr.: One previous statistics course.

    STAT 706. Basic Elements of Statistical Theory. (3) I. The mathematical representation of frequency distributions, their properties, and the theory of estimation and hypothesis testing. Elementary mathematical functions illustrate theory. Pr.: MATH 205, 210, or 220 and STAT 320 or equiv.

    STAT 710. Sample Survey Methods. (2) II, in even years. Design, conduct, and interpretation of sample surveys. Pr.: STAT 702 or 703. Meets four times a week during first half of semester.

    STAT 713. Applied Linear Statistical Models. (3) I. Matrix-based regression and analysis of variance procedures at a mathematical level appropriate for a first-year graduate statistics major. Topics include simple linear regression, linear models in matrix form, multiple linear regression, model building and diagnostics, analysis of covariance, multiple comparison methods, contrasts, multifactor studies, blocking, subsampling, and split-plot designs. Pr.: Prior knowledge of matrix or linear algebra and one prior course in statistics. A student may not receive credit for both STAT 704/705 sequence and STAT 713.

    STAT 716. Nonparametric Statistics. (2) II, in odd years. Hypothesis testing when form of population sampled is unknown: rank, sign, chi-square, and slippage tests; Kolmogorov and Smirnov type tests; confidence intervals and bands. Meets four times a week during second half of semester. Pr.: One previous course in statistics.

    STAT 717. Categorical Data Analysis. (3) II. Analysis of categorical data arranged in two- and higher-dimensional contingency tables using classical methods and log linear models. Various measures of association are discussed. Pr.: STAT 704, 705.

    STAT 720. Design of Experiments. (3) I, S. Planning experiments so as to minimize error variance and avoid bias; Latin squares; split-plot designs; switch-back or reversal designs; incomplete block designs; efficiency. Pr.: STAT 704 and 705.

    STAT 722. Experimental Designs for Product Development and Quality Improvement. (3) II. A study of statistically designed experiments which have proven to be useful in product development and quality improvement. Topics include randomization, blocking, factorial treatment structures, factional factorial designs, screening designs, and response surface methods. Pr.: STAT 511 or STAT 704 and STAT 705.

    STAT 725. Digital Statistical Analysis. (3) II. Techniques of programming in algorithmic languages for statistical applications. Topics include efficiency and numerical accuracy of algorithms, random number generation, Monte Carlo methods, techniques of simulation, and some basic principles of numerical analysis. Pr.: CIS 200 or equiv., STAT 704 and 705.

    STAT 730. Multivariate Statistical Methods. (3) I. Multivariate analysis of variance and covariance; classification and discrimination; principal components and introductory factor analysis; canonical correlation; digital computing procedures applied to data from natural and social sciences. Pr.: STAT 704, 705.

    STAT 736. Bioassay. (2) I, in odd years. Direct assays; quantitative dose-response models; parallel line assays; slope ratio assays; experimental designs for bioassay; covariance adjustment; weighted estimates; assays based on quantal responses. Meets four times a week during second half of semester. Pr.: STAT 704, 705.

    STAT 740. Nonlinear Models. (3) S, in even years. Methods of estimating parameters of nonlinear models; procedures for testing hypotheses; construction of confidence intervals and regions; nonlinear analysis of covariance; quantal dose response and probabilistic choice models. Pr.: MATH 222, STAT 720.

    STAT 745. Graphical Methods, Smoothing, and Regression Analysis. (3) II, in even years. Visual display of quantitative information. Graphical techniques to portray distributions of data, multivariate information, means comparisons, and assessment of distributional assumptions. Data smoothing techniques including loess, parametric, robust, and nonparametric regression, and generalized additive models. Graphical evaluation of smoothing techniques including assessment of assumption. Regression diagnostics.

    STAT 770. Theory of Statistics I. (3) I. Probability models, concepts of probability, random discrete variables, moments and moment generating functions, bivariate distributions, continuous random variables, sampling, Central Limit Theorem, characteristic functions. More emphasis on rigor and proofs than in STAT 510 and 511. Pr.: MATH 222.

    STAT 771. Theory of Statistics II. (3) II. Introduction to multivariate distributions; sampling distributions, derivation, and use; estimation of parameters, testing hypothesis; multiple regression and correlation; simple experimental designs; introduction to nonparametric statistics; discrimination. Pr.: STAT 770.

    STAT 799. Topics in Statistics. (Var.) I, II, S. Pr.: STAT 703 or 770 and consent of instructor.

    Topics within Arts and Sciences:
    dMajors and Degrees dAerospace Studies dMathematics
    dDegree Requirements dAnthropology dMilitary Science
    dBachelor of Arts and Bachelor of Sciences dArt dModern Languages
    dBachelor of Fine Arts dBiochemistry dMusic
    dBachelor of Music dBiology dPhilosophy
    dBachelor of Music Education dChemistry dPhysics
    dAssociate of Arts at Fort Riley dEconomics dPolitical Science
    dAssociate of Science at Fort Riley dEnglish dPsychology
    dProgram Options dGeography dSociology, Anthropology, and Social Work
    dAdvising dGeology dSpeech Communication, Theatre, and Dance
    dUniversity Undergraduate Studies dHistory dStatistics
    dPre-Law dJournalism and Mass Communications   
    dPre-Health Professions Program dKinesiology   
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    Kansas State University
    November 10, 2000