BS in Statistics: Applied Statistics and Analytics Emphasis
(52 hours*)

Program Requirements    |    View MAP

1. No more than three hours of D credit is allowed in major courses.
2. Complete the following preparation core courses:
   MATH 112 : Calculus 1. (4:5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   MATH 112 : Calculus 1. (4:5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   OFFERED:	Honors also.
   WHEN TAUGHT:	Fall; Winter; Spring; Summer
   PREREQUISITE:	Math 110 and 111 or equivalent.
   DESCRIPTION:	Differential and integral calculus: limits; continuity; the derivative and applications; extrema; the definite integral; fundamental theorem of calculus; L'Hopital's rule.
   
             : Honors Calculus 1.
   
   
   Course Outcomes
   
   
   
   MATH 113 : Calculus 2. (4:5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   MATH 113 : Calculus 2. (4:5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   OFFERED:	Honors also.
   WHEN TAUGHT:	Fall; Winter; Spring; Summer
   PREREQUISITE:	Math 112 or equivalent.
   DESCRIPTION:	Techniques and applications of integration; sequences, series, convergence tests, power series; parametric equations; polar coordinates.
   
   
   Course Outcomes
   
   
   
3. Complete one course from the following:
   STAT 121 : Principles of Statistics. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 121 : Principles of Statistics. (3:3:1)(Credit Hours:Lecture Hours:Lab Hours)
   
   OFFERED:	Independent Study also; Honors also.
   WHEN TAUGHT:	Fall; Winter; Spring; Summer
   RECOMMENDED:	MATH 110 or equivalent.
   DESCRIPTION:	Stemplots, boxplots, histograms, scatterplots; central tendency, variability; confidence intervals and hypothesis testing involving one and two means and proportions; contingency tables, simple linear regression.
   
             : Honors Principles of Statistics.
   
   
   Course Outcomes
   
   
   
   STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Spring
   PREREQUISITE:	MATH 112
   RECOMMENDED:	Concurrent enrollment in MATH 113.
   DESCRIPTION:	The scientific method; conditional probability; Bayes' Theorem; conjugate distributions: Beta-binomial, Poisson-gamma, normal-normal; Gibbs sampling.
   
   
   Course Outcomes
   
   
   
   STAT 201 : Statistics for Engineers and Scientists. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 201 : Statistics for Engineers and Scientists. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter; Spring
   PREREQUISITE:	MATH 112; or MATH 119
   DESCRIPTION:	The scientific method; probability, random variables, common discrete and continuous random variables, central limit theorem; confidence intervals and hypothesis testing; completely randomized experiments; factorial experiments.
   
   
   Course Outcomes
   
   
   
   STAT 301 : Statistics and Probability for Secondary Educators. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 301 : Statistics and Probability for Secondary Educators. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Summer
   PREREQUISITE:	MATH 113
   DESCRIPTION:	Statistics and probability, emphasizing secondary-specific curriculum. Principles of counting, probability distributions, density functions, graphical methods, descriptive and inferential statistics, computer package.
   
   
   Course Outcomes
   
   
   
   
   Note: Students who have passed the AP statistics exam or an introductory statistics course should not take Stat 121.
4. Complete the following statistics core courses:
   STAT 124 : SAS Certification 1. (1:1:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 124 : SAS Certification 1. (1:1:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall Blk 1; Winter Blk 1; Spring
   PREREQUISITE:	STAT 121, 151, 201, or 301.
   RECOMMENDED:	Concurrent enrollment in STAT 224.
   DESCRIPTION:	SAS basic programming certification.
   
   
   Course Outcomes
   
   
   
   STAT 125 : SAS Certification 2. (1:1:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 125 : SAS Certification 2. (1:1:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall Blk 2; Winter Blk 2; Summer
   PREREQUISITE:	STAT 124
   RECOMMENDED:	Concurrent enrollment in STAT 224.
   DESCRIPTION:	Advanced SAS programming certification.
   
   
   Course Outcomes
   
   
   
   STAT 224 : Statistical Computing 1. (2:0:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 224 : Statistical Computing 1. (2:0:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter; Summer
   PREREQUISITE:	STAT 124 or concurrent enrollment.
   DESCRIPTION:	Statistical programming using the data step in SAS; basic Procs; Proc MEAN, SORT, TABULATE, SQL, and REPORT; ODS; simple MACROS.
   
   
   Course Outcomes
   
   
   
   STAT 230 : Analysis of Variance. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 230 : Analysis of Variance. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter; Spring
   PREREQUISITE:	STAT 121, 151, 201, or 301.
   RECOMMENDED:	Concurrent enrollment in MATH 112.
   DESCRIPTION:	Scientific method, statistical thinking, sources of variation, completely randomized design, ANOVA, power and sample size considerations, multiple testing, randomized complete blocks, factorial designs, interactions. Introduction to statistical software.
   
   
   Course Outcomes
   
   
   
   STAT 240 : Discrete Probability. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 240 : Discrete Probability. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter; Summer
   PREREQUISITE:	MATH 112 or concurrent enrollment; concurrent enrollment in MATH 113; STAT 121 or 151 or 201 or 301.
   DESCRIPTION:	Set theory; discrete probability; conditional probability; finite sample spaces; discrete random variables (pdf, cdf, moments).
   
   
   Course Outcomes
   
   
   
   STAT 290 : Communication of Statistical Results. (1:1:1)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 290 : Communication of Statistical Results. (1:1:1)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter
   PREREQUISITE:	STAT 230; First-Year Writing.
   DESCRIPTION:	Introduction to writing within the discipline including the effective use of graphics, tables, and equations. Resources and guidelines for writing and presenting statistical results.
   
   
   Course Outcomes
   
   
   
   STAT 330 : Introduction to Regression. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 330 : Introduction to Regression. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter
   PREREQUISITE:	STAT 230 & MATH 112
   RECOMMENDED:	MATH 113 or concurrent enrollment.
   DESCRIPTION:	Regression, transformations, residuals, indicator variables, variable selection, logistic regression, time series, observational studies, statistical software.
   
   
   Course Outcomes
   
   
   
   STAT 340 : Inference. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 340 : Inference. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter
   PREREQUISITE:	STAT 240 & MATH 113
   DESCRIPTION:	Continuous random variables (pdf, cdf, mgf, moments); sampling distributions; Central Limit Theorem; frequentist inference (estimation, intervals, hypothesis tests); Bayesian inference (estimation, intervals); simulation.
   
   
   Course Outcomes
   
   
   
5. Complete the following:
   ECON 110 : Economic Principles and Problems. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   ECON 110 : Economic Principles and Problems. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   OFFERED:	Honors also.
   WHEN TAUGHT:	Fall; Winter; Spring; Summer
   DESCRIPTION:	Strengths and weaknesses of markets and governments for solving problems of social organization or conflict, including policy response to inflation, unemployment, pollution, poverty, growth, etc.
   NOTE:	This course is part of a GE Mosaic. See ge.byu.edu/mosaic-list for more information.
   
             : Honors Economic Principles and Problems.
   
   
   Course Outcomes
   
   
   
   STAT 424 : Statistical Computing 2. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 424 : Statistical Computing 2. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 224 & STAT 330
   DESCRIPTION:	S Plus, statistical graphics, simulation, advanced SAS (macros, Proc IML, and Proc SQL), and database programming.
   
   
   Course Outcomes
   
   
   
6. Complete 18 credit hours from the following:
   C S 142 : Introduction to Computer Programming. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   C S 142 : Introduction to Computer Programming. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Winter; Spring
   PREREQUISITE:	Knowledge of algebra.
   DESCRIPTION:	Introduction to object-oriented program design and development. Principles of algorithm formulation and implementation.
   
   
   Course Outcomes
   
   
   
   STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 151 : Introduction to Bayesian Statistics. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall; Spring
   PREREQUISITE:	MATH 112
   RECOMMENDED:	Concurrent enrollment in MATH 113.
   DESCRIPTION:	The scientific method; conditional probability; Bayes' Theorem; conjugate distributions: Beta-binomial, Poisson-gamma, normal-normal; Gibbs sampling.
   
   
   Course Outcomes
   
   
   
   STAT 234 : Methods of Survey Sampling. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 234 : Methods of Survey Sampling. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall
   PREREQUISITE:	STAT 121, 151, 201, or 301.
   DESCRIPTION:	Sampling frames, questionnaire design; simple random, systematic, stratified, and cluster sampling methods, comparing domain means, contingency table analysis.
   
   
   Course Outcomes
   
   
   
   STAT 341 : Statistical Theory 1. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 341 : Statistical Theory 1. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall
   PREREQUISITE:	MATH 314; Stat 121, 151, 201, or 301.
   DESCRIPTION:	Axiomatic probability theory for discrete and continuous random variables; moment-generating functions; conditional probability; stochastic independence; transformations; limiting distributions; stochastic convergence; central limit theorem.
   
   
   Course Outcomes
   
   
   
   STAT 342 : Statistical Theory 2. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 342 : Statistical Theory 2. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 341
   DESCRIPTION:	Sufficiency and completeness; point and interval estimation; hypothesis testing; Cramer-Rao inequality; some asymptotic results; Bayesian methods.
   
   
   Course Outcomes
   
   
   
   STAT 431 : Experimental Design. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 431 : Experimental Design. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall
   PREREQUISITE:	STAT 330
   DESCRIPTION:	Basic designs, power and sample size, Latin squares, incomplete blocks, change-over designs, factorials, fractional factorials, confounding, split-plots, response surface designs.
   
   
   Course Outcomes
   
   
   
   STAT 435 : Nonparametric Statistical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 435 : Nonparametric Statistical Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 330; or STAT 511
   DESCRIPTION:	Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, curve fitting.
   
   
   Course Outcomes
   
   
   
   STAT 462 : Quality Control and Industrial Statistics. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 462 : Quality Control and Industrial Statistics. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall
   PREREQUISITE:	STAT 330 & STAT 340
   DESCRIPTION:	Six sigma; tools with which to define, measure, analyze, improve, control. Advanced concepts in control charts, applying experimental design for process and product improvement.
   
   
   Course Outcomes
   
   
   
   STAT 466 : Introduction to Reliability. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 466 : Introduction to Reliability. (3:3:2)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 330; or STAT 340
   DESCRIPTION:	Mathematics, distributions, management, and maintenance of basic reliability concepts; collection and analysis of test data; fault tree analysis; applying reliability in various areas.
   
   
   Course Outcomes
   
   
   
   STAT 469 : Applied Time Series and Forecasting. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 469 : Applied Time Series and Forecasting. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   PREREQUISITE:	STAT 330 & STAT 340
   DESCRIPTION:	Data mining, univariate ARIMA time series theory and application, seasonal models, spatial correlation models, conditional heteroscedastic models in financial time series, case studies.
   
   
   Course Outcomes
   
   
   
   STAT 474 : Theory of Interest. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 474 : Theory of Interest. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 370
   DESCRIPTION:	Theory of interest, annuities, amortization, financial derivatives. Prepares for the Society of Actuaries Exam FM.
   
   
   Course Outcomes
   
   
   
   STAT 496R : Academic Internship: Statistics. (.5-9:ARR:ARR)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 496R : Academic Internship: Statistics. (.5-9:ARR:ARR)(Credit Hours:Lecture Hours:Lab Hours)
   
   PREREQUISITE:	Department coordinator's consent.
   DESCRIPTION:	On-the-job experience or internships for undergraduates. Report is required.
   
   
   Course Outcomes
   
   
   
   STAT 497R : Introduction to Statistical Research. (.5-3:0:6)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 497R : Introduction to Statistical Research. (.5-3:0:6)(Credit Hours:Lecture Hours:Lab Hours)
   
   PREREQUISITE:	Department chair's consent.
   DESCRIPTION:	Review of current literature and survey of present status of significant statistical research; collaborative work between student and faculty.
   
   
   Course Outcomes
   
   
   
   STAT 499R : Honors Thesis. (.5-6:ARR:ARR)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 499R : Honors Thesis. (.5-6:ARR:ARR)(Credit Hours:Lecture Hours:Lab Hours)
   
   PREREQUISITE:

   Departmental consent.
   
   
   Course Outcomes
   
   
   
   STAT 500 : (Stat-Chem-C S-Geol-Math-MthEd-Phscs) Business Career Essentials in Science and Math. (1.5:1.5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 500 : (Stat-Chem-C S-Geol-Math-MthEd-Phscs) Business Career Essentials in Science and Math. (1.5:1.5:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   DESCRIPTION:	Introduction for science, math, and statistics majors to careers in industry. Project planning, oral and written business presentations, business accounting, and technology readiness.
   
   
   Course Outcomes
   
   
   
   STAT 535 : Applied Linear Models. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 535 : Applied Linear Models. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Fall
   PREREQUISITE:	Departmental consent.
   DESCRIPTION:	Theory of estimation and testing in linear models. Analysis of full-rank model, over-parameterized model, cell-means model, unequal subclass frequencies, and missing and fused cells. Estimability issues, diagnostics.
   
   
   Course Outcomes
   
   
   
   STAT 536 : Modern Regression Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 536 : Modern Regression Methods. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 535, 624; or departmental consent.
   DESCRIPTION:	Weighted least squares, Bayesian linear models, robust regression, nonlinear regression, local regression, generalized additive models, tree-structured regression.
   
   
   Course Outcomes
   
   
   
   STAT 537 : Generalized Linear Models. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 537 : Generalized Linear Models. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 535 & STAT 642
   DESCRIPTION:	Generalized linear models framework, binary data, polytomous data, log-linear models.
   
   
   Course Outcomes
   
   
   
   STAT 538 : Survival Analysis. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   STAT 538 : Survival Analysis. (3:3:0)(Credit Hours:Lecture Hours:Lab Hours)
   
   WHEN TAUGHT:	Winter
   PREREQUISITE:	STAT 341
   DESCRIPTION:	Basic concepts of survival analysis; hazard functions; types of censoring; Kaplan-Meier estimates; Logrank tests; proportional hazard models; examples drawn from clinical and epidemiological literature.
   
   
   Course Outcomes
   
   
   
   
   

   Note: Students interested in quality improvement are strongly recommended to take Stat 431, 462, 466.

*Hours include courses that may fulfill university core requirements.

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