Stat 210 — Statistical Software
In sample path3 unitsDatabase management and programming using statistical software.
Area of concentration
Industrial Statistics
Statistics for manufacturing, quality and reliability
15
electives to choose from
5
electives you'll take (15 units)
6
courses only in this track
8
shared with Statistical Methods for Market Research
Focuses on the methods industry uses to design processes, keep quality in control and measure how long products last. Expect designed experiments, control charts and process capability, response surface optimization, survival and reliability analysis, and Six Sigma.
Key topics
Design of experimentsStatistical process controlProcess capabilityResponse surface optimizationReliability and survivalSix SigmaAcceptance samplingNonparametric methods
Good fit for
Quality assurance and process improvementManufacturing and engineering analyticsProduct testing and reliability
Recommended background
Comfort with regression (Stat 223) and basic inference. Interest in how products and processes are made helps more than heavy theory.
Related tracks
Electives shared with this track
Only in this track: Stat 244, Stat 245, Stat 246, Stat 271, Stat 272, Stat 273
Track profiles are guidance written for this dashboard, not official university text.
Sample path
Core courses are fixed; the five highlighted electives are one way to fill your elective slots in this track. Offerings vary by semester, so confirm your plan with your adviser.
Year 1 · 1st Sem
9 units
- Stat 2213u
Introductory Probability
- Stat 2103u
Statistical Software
- Stat 2243u
Experimental Designs
Year 1 · 2nd Sem
9 units
- Stat 2223u
Introduction to Statistical Inference
- Stat 2233u
Applied Regression Analysis
- Stat 2713u
Statistical Quality Control
Year 2 · 1st Sem
10 units
- Stat 2503u
Sampling Designs
- Stat 2901u
Statistical Consulting
- Stat 2453u
Survival Analysis
- Stat 2463u
Response Surface Methods
Year 2 · 2nd Sem
9 units
- Stat 2513u
Survey Operations
- Stat 2901u
Statistical Consulting
- Stat 2985u
Special Problem
Total 37 units: 22 core + 15 elective (5 × 3 units).
Electives in Industrial Statistics
15 courses, all 3 units. Choose any five; the ones marked “In sample path” are used above.
Stat 211 — Statistical Computing
3 unitsAlgorithms for statistical computing; numerical analysis for linear and nonlinear models; random number generation; Monte Carlo methods.
Stat 224 — Experimental Designs
In sample path3 unitsCompletely randomized designs; randomized complete block design; Latin square design; factorial experiments; incomplete block design; higher-order designs.
Prereq: Stat 223/233/equiv/COI.
Stat 241 — Nonlinear Regression
3 unitsClassification of nonlinear models; iterative estimation and linear approximation; practical considerations: model specification, starting values, transformations; convergence; multiresponse model; models from differential equations; nonlinear inference regions; measures of nonlinearity; applications.
Prereq: Stat 218/223/233/equiv/COI.
Stat 243 — Categorical Data Analysis
3 unitsCross-classified tables, multidimensional tables; loglinear model; logit models, measures of association; inference for categorical data; applications.
Prereq: Stat 223/233/equiv/COI.
Stat 244 — Design and Analysis of Clinical Experiments
3 unitsReliability of measurements; parallel groups design; control of prognostic factors; blocking and stratification; analysis of covariance; repeated measurements and crossover studies; balanced incomplete block designs; factorial experiments; split-plot designs; applications.
Prereq: Stat 223/233/ equiv/COI.
Stat 245 — Survival Analysis
In sample path3 unitsFunctions of survival time; estimation of survival functions; survival distributions and their applications; distribution fitting and goodness-of-fit tests.
Prereq: Stat 207/222/232/equiv/COI.
Stat 246 — Response Surface Methods
In sample path3 unitsProduct design and development; optimal designs; response surface models; response surface optimization; applications.
Prereq: Stat 223/233/equiv/COI.
Stat 266 — Applied Nonparametric Methods
3 unitsMethods for single, two and k samples; trends and association; nonparametric bootstrap.
Prereq: Stat 222/equiv/COI, Stat 223/equiv/COI.
Stat 269 — Advanced Categorical Data Analysis
3 unitsProbability structure of categorical data; modeling count data with heterogeneous mean; models for multinomial responses; postulation, estimation, evaluation of various parametrization of models for categorical data; assessment and handling of overdispersion in count data; clustered categorical data; advanced topics.
Prereq: Stat 207/243/equiv/COI.
Stat 270 — Exploratory Data Analysis
3 unitsGraphical methods; single batch analysis and analysis of several batches; order Statistics; resistant estimators; robust tests; robust regression; median polish; applications.
Prereq: Stat 222/232/equiv/COI.
Stat 271 — Statistical Quality Control
In sample path3 unitsOverview of statistical methods useful in quality assurance; statistical process control; control charts for variables and attributes, cusum chart, multivariate chart; process capability analysis; acceptance sampling; MIL STD tables and JIS tables; off-line quality control; introduction to response surface analysis; Taguchi method; applications.
Prereq: Stat 222/232/equiv/COI.
Stat 272 — Reliability Theory
3 unitsCoherent systems; paths and cuts, life distribution; dependent components; maintenance policies and replacement models; domains of attraction.
Prereq: Stat 231.
Stat 273 — Six Sigma Statistics
3 unitsDMAIC (define-measure-analyze-improve-control) methodology; statistical process control; process capability; failure mode and effects analysis (FMEA); measurement system analysis; optimization by experimentation; Taguchi method.
Prereq: COI.
Stat 276 — Statistics for Geographic Information Systems
3 unitsComponents of a geographical information system, data structures and elements of spatial modeling; exploratory spatial data analysis; quadrat analysis, tesselations and spatial autocorrelation; spatial modeling and prediction; some sampling theory; applications.
Prereq: COI.