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Penn State Statistics Courses

These are the Penn State statistics courses that we tutor. If you don't see a course listed in which you need help, e.g. a statistically intensive course offered at Penn State outside of the Statistics Department or a course at another school, fill out the consultation request form and provide details of your situation in the area provided for additional information.

Click the course number and name to expand the course description.

Course Number & Name
Open  Stat 100 Statistical Concepts and Reasoning Close  Stat 100 (GQ)   Statitical Concepts and Reasoning   (3)

Introduction to the art and science of decision making in the presence of uncertainty.

General Education: GQ
Diversity: None
Bachelor of Arts: Quantification
Effective: Summer 1988

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 200   Elementary Statistics Close  Stat 200 (GQ)   Elementary Statistics   (4)

Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.

(BA) This course meets the Bachelor of Arts degree requirements.

STAT 200 is a standard first course in statistics. Students who have successfully completed this course will understand basic concepts of probability and statistical inference, including common graphical and numerical data summaries; notions of sampling from a population of interest, including the sampling distribution of a statistic; construction and interpretation of confidence intervals, test statistics, and p-values; and connections between probabilistic concepts like the normal distribution and statistical inference. They will recognize various types of data, appropriate statistical methods to analyze them, and assumptions that underlie these methods. They will also gain extensive experience in the use of statistical software to analyze data and the interpretation the output of this software.


General Education: GQ
Diversity: None
Bachelor of Arts: Quantification
Effective: Fall 2014
Prerequisite: Placement into MATH 021 or higher

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 200H   Elementary Statistics Close  Stat 200H (GQ)   Basic Statistics (4)

Descriptive statistics, frequency distributions, probability, binomial and normal distributions, statistical inference, linear regression, and correlation.

General Education: GQ
Diversity: None
Bachelor of Arts: Quantification
Effective: Fall 2015 Ending: Fall 2015 Future: Fall 2015
Prerequisite: Placement into MATH 021 or higher

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 301   Statistical Analysis Close  Stat 301 (GQ)   Statistical Analysis (3)

Probability concepts; nature of statistical methods; elementary distribution and sampling theory; fundamental ideas relative to estimation and testing hypotheses.

General Education: GQ
Diversity: None
Bachelor of Arts: Quantification
Effective: Summer 1988
Prerequisite: 3 credits of calculus

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 318   Elementary Probability Close  Stat 318 (Math 318)   Elementary Probability (3)

Combinatorial analysis, axioms of probability, conditional probability and independence, discrete and continuous random variables, expectation, limit theorems, additional topics.

Students who have passed either STAT(MATH) 414 or 418 may not schedule this course for credit.

General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 1989
Prerequisite: MATH 141

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 319   Applied Statistics in Science Close  Stat 319 (Math 319)   Applied Statistics in Science (3)

Statistical inference: principles and methods, estimation and testing hypotheses, regression and correlation analysis, analysis of variance, computer analysis.

Students who have passed STAT (MATH) 415 may not schedule this course for credit.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 1989
Prerequisite: STAT 318 or knowledge of basic probability

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 401   Experimental Methods Close  Stat 401   Experimental Methods (3)

Random variables; probability density functions; estimation; statistical tests, t-tests; correlation; simple linear regression; one-way analysis of variance; randomized blocks.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 1988
Prerequisite: MATH 111 or MATH 141

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 414   Introduction to Probability Theory Close  Stat 414 (Math 414)   Introduction to Probability Theory (3)

Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems.

Students may take only one course from STAT(MATH) 414 and 418.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 2001
Prerequisite: MATH 230 or MATH 231

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 415   Introduction to Mathematical Statistics Close  Stat 415 (Math 415)   Introduction to Mathematical Statistics (3)

A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 1989
Prerequisite: MATH 414

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 416   Stochastic Modeling Close  Stat 416 (Math 416)   Stochastic Modeling (3)

Review of distribution models, probability generating functions, transforms, convolutions, Markov chains, equilibrium distributions, Poisson process, birth and death processes, estimation.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 1984
Prerequisite: STAT 318 or STAT 414; MATH 230

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 418   Introduction to Probability and Stochastic Processes for Engineering Close  Stat 418 (Math 418)   Introduction to Probability and Stochastic Processes for Engineering (3)

Introduction to probability axioms, combinatorics, random variables, limit laws, and stochastic processes. Students may take only one course from MATH(STAT) 414 and 418 for credit.

This course gives an introduction to probability and random processes. The topics are not covered as deeply as in a semester-long course in probability only or in a semester-long course in stochastic processes only. It is intended as a service course primarily for engineering students, though no engineering background is required or assumed.

The topics covered include probability axioms, conditional probability, and combinatorics; discrete random variables; random variables with continuous distributions; jointly distributed random variables and random vectors; sums of random variables and moment generating functions; and stochastic processes, including Poisson, Brownian motion, and Gaussian processes.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 2011
Prerequisite: MATH 230 or MATH 231

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 460   Intermediate Applied Statistics Close  Stat 460   Intermediate Applied Statistics (3)

Review of hypothesis testing, goodness-of-fit tests, regression, correlation analysis, completely randomized designs, randomized complete block designs, latin squares.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Summer 2015
Prerequisite: STAT 200, STAT 240,STAT 250, STAT 301 or STAT 401

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 462   Applied Regression Analysis Close  Stat 462   Applied Regression Analysis (3)

Introduction to linear and multiple regression; correlation; choice of models, stepwise regression, nonlinear regression.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Summer 2015
Prerequisite: STAT 200, STAT 240, STAT 250, STAT 301 or STAT 401

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 500   Applied Statistics Close  Stat 500   Applied Statistics (3)

Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and 2-way ANOVA, Chi-square tests, diagnostics.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 1999
Prerequisite: one undergraduate course in statistics

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 501   Regression Methods Close  Stat 501   Regression Methods (3)

Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 2006
Prerequisite: STAT 500 or equivalent; matrix algebra

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 502   Analysis of Variance and Design of Experiments Close  Stat 502   Analysis of Variance and Design of Experiments (3)

Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 1995
Prerequisite: STAT 462 or STAT 501

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 513   Theory of Statistics I Close  Stat 513   Theory of Statistics I (3)

Probability models, random variables, expectation, generating functions, distribution theory, limit theorems, parametric families, exponential families, sampling distributions.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Summer 1986
Prerequisite: MATH 230

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 514   Theroy of Statistics II Close  Stat 514   Theory of Statistics II (3)

Sufficiency, completeness, likelihood, estimation, testing, decision theory, Bayesian inference, sequential procedures, multivariate distributions and inference, nonparametric inference.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Summer 1986
Prerequisite: STAT 513

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 515   Stochastic Processes and Monte Carlo Methods Close  Stat 515   Stochastic Processes and Monte Carlo Methods (3)

Conditional probability and expectation, Markov chains, Poisson processes, Continuous-time Markov chains, Monte Carlo methods, Markov chain Monte Carlo.

This course provides an introduction to stochastic processes and Monte Carlo methods. The course covers topics usually covered in a standard introductory course on stochastic processes, including Markov chains of various kinds. It also covers modern Monte Carlo and Markov chain Monte Carlo methods. Simulation and computing are emphasized throughout the course.

The course is divided into two parts: the first part (roughly 8 weeks) provides an introduction to stochastic processes, while the latter (roughly 7 weeks) focuses on Monte Carlo methods, including Markov chain Monte Carlo. The first part of the course begins with a review of elementary conditional probability and expectation before covering basic discrete-time Markov chain theory and Poisson processes. The course then provides students with an overview of continuous-time Markov chains and birth-death processes. The second part of the course covers Monte Carlo methods. Starting with basic random variate generation, the course covers classical Monte Carlo methods such as accept-reject and importance sampling before discussing Markov chain Monte Carlo (MCMC) methods, which includes the Metropolis-Hastings and Gibbs sampling algorithms, and Markov chain theory for discrete-time continuous-space Markov chains.


General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Spring 2013
Prerequisite: MATH 414, STAT 414 or STAT 513

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 517   Probability Theory Close  Stat 517 (Math 517)   Applied Statistics (3)

Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability,special topics.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Summer 2000
Prerequisite: MATH 403

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Open  Stat 518   Probability Theory Close  Stat 518 (Math 518)   Probability Theory (3)

Measure theoretic foundation of probability, distribution functions and laws, types of convergence, central limit problem, conditional probability, special topics.



General Education: None
Diversity: None
Bachelor of Arts: None
Effective: Fall 1983
Prerequisite: STAT 517

Note : Class size, frequency of offering, and evaluation methods will vary by location and instructor. For these details check the specific course syllabus.

Course Descriptions are taken from the Penn State Undergraduate and Graduate Bulletins and are provided for convenience only. Please, refer to these bulletins for official purposes.
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