Undergraduate Course Descriptions
Highlighted courses are being taught in Fall 2009.
STAT 113 Statistics and Society (Banner Course Number: 11300)
Semester: Fall Spring
Prerequisites: None
Credits: 3
Primary Audience: Liberal Arts. Not available for credit in College of Science.
Description: Offered Maymester as 113K. A course on statistical concepts emphasizing applications in public policy and in the social and behavioral sciences. Much writing and discussion are required. No mathematics beyond simple algebra is needed, but numerical skills are strengthened by constant use. STAT 113 can be used for general education or as preparation for later methodology courses. Teaches statistical ideas that will be useful in understanding and designing research in most areas of study.
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Semester: Fall Spring
Prerequisites: None
Credits: 3
Primary Audience: Liberal Arts. Not available for credit in College of Science.
Description: Offered Maymester as 113K. A course on statistical concepts emphasizing applications in public policy and in the social and behavioral sciences. Much writing and discussion are required. No mathematics beyond simple algebra is needed, but numerical skills are strengthened by constant use. STAT 113 can be used for general education or as preparation for later methodology courses. Teaches statistical ideas that will be useful in understanding and designing research in most areas of study.
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STAT 113K.SUM09 Statistics and Society (Banner Course Number: 11300)
Semester: Summer
Prerequisites: None
Credits: 3
Primary Audience: Liberal Arts. Not available for credit in College of Science.
Description: This course is only offered during MAYMESTER. During Fall and Spring it is offered as 113. A course on statistical concepts emphasizing applications in public policy and in the social and behavioral sciences. Much writing and discussion are required. No mathematics beyond simple algebra is needed, but numerical skills are strengthened by constant use. STAT 113K can be used for general education or as preparation for later methodology courses. Teaches statistical ideas that will be useful in understanding and designing research in most areas of study.
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Semester: Summer
Prerequisites: None
Credits: 3
Primary Audience: Liberal Arts. Not available for credit in College of Science.
Description: This course is only offered during MAYMESTER. During Fall and Spring it is offered as 113. A course on statistical concepts emphasizing applications in public policy and in the social and behavioral sciences. Much writing and discussion are required. No mathematics beyond simple algebra is needed, but numerical skills are strengthened by constant use. STAT 113K can be used for general education or as preparation for later methodology courses. Teaches statistical ideas that will be useful in understanding and designing research in most areas of study.
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STAT 170 Introduction to Actuarial Science (MA 170) (Banner Course Number: 17000)
Semester: Fall
Prerequisites: (or Corequisite): MATH 162 or equivalent
Credits: 2
Primary Audience: Actuarial Science
Description: An introduction to Actuarial Science from the point of view of practicing actuaries from life insurance, casualty insurance, and consulting; mathematical theory of interest; applications of calculators and computers to problems involving interest.
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Semester: Fall
Prerequisites: (or Corequisite): MATH 162 or equivalent
Credits: 2
Primary Audience: Actuarial Science
Description: An introduction to Actuarial Science from the point of view of practicing actuaries from life insurance, casualty insurance, and consulting; mathematical theory of interest; applications of calculators and computers to problems involving interest.
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STAT 190 Topics in Statistics for Undergraduates (Banner Course Number: 19000)
Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 190 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the freshman undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 190 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the freshman undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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STAT 225 Introduction to Probability Models (Banner Course Number: 22500)
Semester: Fall Spring Summer
Prerequisites: MA 224 or MA 161 or its equivalent.
Credits: 3
Primary Audience: Management.
Description: Probability theory with emphasis on the use of probability models in applications. Requires a year of calculus at the level of MATH 223-224. Does not cover statistical methods.
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Semester: Fall Spring Summer
Prerequisites: MA 224 or MA 161 or its equivalent.
Credits: 3
Primary Audience: Management.
Description: Probability theory with emphasis on the use of probability models in applications. Requires a year of calculus at the level of MATH 223-224. Does not cover statistical methods.
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STAT 250 Problem Solving in Probability (Banner Course Number: 25000)
Semester: Fall
Prerequisites: MA/STAT 416 is strongly recommended.
Credits: 2
Primary Audience: Actuarial Science majors
Description: This course is designed to teach techniques for solving problems in probability theory which are relevant to the actuarial sciences. It is intended to help actuarial students prepare for the Society of Actuaries and Casualty Actuarial Society Exam P/1.
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Semester: Fall
Prerequisites: MA/STAT 416 is strongly recommended.
Credits: 2
Primary Audience: Actuarial Science majors
Description: This course is designed to teach techniques for solving problems in probability theory which are relevant to the actuarial sciences. It is intended to help actuarial students prepare for the Society of Actuaries and Casualty Actuarial Society Exam P/1.
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STAT 290 Topics in Statistics for Undergraduates (Banner Course Number: 29000)
Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 290 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the sophomore undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 290 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the sophomore undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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STAT 301 Elementary Statistical Methods (Banner Course Number: 30100)
Semester: Fall Spring Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: Offered in Maymester as 301K. An Honors section is available as 301H. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout.
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Semester: Fall Spring Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: Offered in Maymester as 301K. An Honors section is available as 301H. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout.
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STAT 301H Elementary Statistical Methods (Banner Course Number: 30100)
Semester: Fall Spring Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: This is the Honors section of 301. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout. Honors STAT 301 students will complete several diverse outside-of-class projects to complete their honors requirement. The course website, under Honors STAT 301, will give specific details about these projects.
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Semester: Fall Spring Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: This is the Honors section of 301. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout. Honors STAT 301 students will complete several diverse outside-of-class projects to complete their honors requirement. The course website, under Honors STAT 301, will give specific details about these projects.
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STAT 301K.SUM09 Elementary Statistical Methods (Banner Course Number: 30100)
Semester: Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: This course is offered during MAYMESTER. During Fall, Spring, and Summer it is offered as 301. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout.
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Semester: Summer
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering.
Description: This course is offered during MAYMESTER. During Fall, Spring, and Summer it is offered as 301. Introduction to statistical methods with applications to diverse fields. Emphasis on understanding and interpreting standard techniques. Data analysis for one and several variables, design of samples and experiments, basic probability, sampling distributions, confidence intervals and significance tests for means and proportions, correlation and regression. Software is used throughout.
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STAT 301Y Elementary Statistical Methods (Banner Course Number: 30100)
Semester: Fall Spring
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering
Description: An online version of STAT 301 that covers the same material. Methods of applied statistics for undergraduates with good algebra but no alculus. Emphasizes working with data and understanding the essential ideas and methods of applied statistics. Includes experience with the statistical techniques within the software package SPSS. Course meets in virtual computer lab once a week. Primarily intended for students who will take only one statistics course.
Students enrolled in 301Y should contact the course coordinator, Ellen Gundlach, by email: gundlach@stat.purdue.edu.
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Semester: Fall Spring
Prerequisites: MA 153 and 154, or equivalent algebra and trigonometry.
Credits: 3
Primary Audience: Agriculture, CFS, Health Science, Mathematical Sciences, or Engineering
Description: An online version of STAT 301 that covers the same material. Methods of applied statistics for undergraduates with good algebra but no alculus. Emphasizes working with data and understanding the essential ideas and methods of applied statistics. Includes experience with the statistical techniques within the software package SPSS. Course meets in virtual computer lab once a week. Primarily intended for students who will take only one statistics course.
Students enrolled in 301Y should contact the course coordinator, Ellen Gundlach, by email: gundlach@stat.purdue.edu.
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STAT 311 Introductory Probability (Banner Course Number: 31100)
Semester: Fall Spring
Prerequisites: MATH 161-162 or equivalent.
Credits: 3
Primary Audience: Mathematics education.
Description: Primarily probability theory, but with a brief introduction to statistics. Requires a year of calculus at the MATH 161-162 level. Does not contain enough statistics to serve as preparation for second courses in statistics such as STAT 502 and 512. Intended primarily for mathematics education majors. Taught Spring Semester Only.
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Semester: Fall Spring
Prerequisites: MATH 161-162 or equivalent.
Credits: 3
Primary Audience: Mathematics education.
Description: Primarily probability theory, but with a brief introduction to statistics. Requires a year of calculus at the MATH 161-162 level. Does not contain enough statistics to serve as preparation for second courses in statistics such as STAT 502 and 512. Intended primarily for mathematics education majors. Taught Spring Semester Only.
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STAT 350 Introduction to Statistics (Banner Course Number: 35000)
Semester: Fall Spring
Prerequisites: MATH 161-162 or equivalent.
Credits: 3
Primary Audience: Acturial Science, Mathematics, Mathematics Education, or Statistics.
Description: A data-oriented introduction to the fundamental concepts and methods of applied statistics. STAT 350 is intended primarily for majors in the mathematical sciences (Actuarial Science, Mathematics, Mathematics Education, or Statistics). It covers material similar to that of STAT 511 (for engineering and physical sciences). Students from these majors may take STAT 350 if space is available. STAT 350 is more software-intensive and covers more data-analytic material or STAT 511, but does less formal probability.
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Semester: Fall Spring
Prerequisites: MATH 161-162 or equivalent.
Credits: 3
Primary Audience: Acturial Science, Mathematics, Mathematics Education, or Statistics.
Description: A data-oriented introduction to the fundamental concepts and methods of applied statistics. STAT 350 is intended primarily for majors in the mathematical sciences (Actuarial Science, Mathematics, Mathematics Education, or Statistics). It covers material similar to that of STAT 511 (for engineering and physical sciences). Students from these majors may take STAT 350 if space is available. STAT 350 is more software-intensive and covers more data-analytic material or STAT 511, but does less formal probability.
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STAT 390 Topics in Statistics for Undergraduates (Banner Course Number: 39000)
Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 390 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the junior undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: STAT 390 will consist of readings, discussions, written reports and/or data analyses on special topics in statistics and probability, arranged as a reading course or as a class with regular meetings, at the junior undergraduate level, under the supervision of a faculty member for the enrichment of the student's knowledge in the statistical sciences. Consent of the instructor is required.
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HONR 399 "Lies, Damned Lies, and Statistics" (Banner Course Number: 39900)
Semester: Fall
Prerequisites: None.
Credits: 3
Primary Audience: The course is intended for sophomores, juniors, and seniors from all disciplines who are interested in making persuasive arguments using data.
Description: We are constantly exposed to massive amounts of information via the computer (email, text messaging, chatting, and social networking sites such as Facebook and MySpace). Some sources are enlightening and convincing while others are deliberately misleading. How do we discern the veracity of messages when faced with the onslaught of digital information so prevalent in the digital age? How can we convey our own information in the most persuasive and effective manner?
This course will enable students to use the computer to analyze, understand, and interpret data, with an emphasis on the visual display of quantitative information. We will begin the course with a survey of data representations. Next we will study how data can be utilized and extracted in various formats. We will use hands-on computational tools to manipulate data and transform it from one representation to another. Examples of data to be considered might include online maps and satellite imagery; genetic sequences; election results; literary texts; airline scheduling; social and environmental data.
The course will be project-oriented. Students will gain practical experience with a variety of tools for interpreting data using the computer. The key goal of the course is to empower students with skills for: advocating a cause, making persuasive arguments, educating consumers, planning strategies, and communicating ideas in innovative and compelling ways.
The skills learned in this course will be useful to students from nearly every discipline. No prior computational or statistical experience is necessary.
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Semester: Fall
Prerequisites: None.
Credits: 3
Primary Audience: The course is intended for sophomores, juniors, and seniors from all disciplines who are interested in making persuasive arguments using data.
Description: We are constantly exposed to massive amounts of information via the computer (email, text messaging, chatting, and social networking sites such as Facebook and MySpace). Some sources are enlightening and convincing while others are deliberately misleading. How do we discern the veracity of messages when faced with the onslaught of digital information so prevalent in the digital age? How can we convey our own information in the most persuasive and effective manner?
This course will enable students to use the computer to analyze, understand, and interpret data, with an emphasis on the visual display of quantitative information. We will begin the course with a survey of data representations. Next we will study how data can be utilized and extracted in various formats. We will use hands-on computational tools to manipulate data and transform it from one representation to another. Examples of data to be considered might include online maps and satellite imagery; genetic sequences; election results; literary texts; airline scheduling; social and environmental data.
The course will be project-oriented. Students will gain practical experience with a variety of tools for interpreting data using the computer. The key goal of the course is to empower students with skills for: advocating a cause, making persuasive arguments, educating consumers, planning strategies, and communicating ideas in innovative and compelling ways.
The skills learned in this course will be useful to students from nearly every discipline. No prior computational or statistical experience is necessary.
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STAT 416 Probability (MA 416) (Banner Course Number: 41600)
Semester: Fall Spring
Prerequisites: MATH 174, 261 or equivalent
Credits: 3
Primary Audience: Actuarial Science, Mathematics, Statistics.
Description: An introduction to mathematical probability suitable as preparation for actuarial science, statistical theory, and mathematical modeling. General probability rules, conditional probability, and Bayes theorem, discrete and continuous random variables, moments and moment generating functions, joint and conditional distributions, standard discrete and continuous distributions and their properties, law of large numbers and central limit theorem.
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Semester: Fall Spring
Prerequisites: MATH 174, 261 or equivalent
Credits: 3
Primary Audience: Actuarial Science, Mathematics, Statistics.
Description: An introduction to mathematical probability suitable as preparation for actuarial science, statistical theory, and mathematical modeling. General probability rules, conditional probability, and Bayes theorem, discrete and continuous random variables, moments and moment generating functions, joint and conditional distributions, standard discrete and continuous distributions and their properties, law of large numbers and central limit theorem.
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STAT 417 Statistical Theory (Banner Course Number: 41700)
Semester: Fall Spring
Prerequisites: MATH/STAT 416 or equivalent. STAT 350 or equivalent is desirable.
Credits: 3
Primary Audience: Actuarial Science, Mathematics, Statistics.
Description: An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Most powerful and likelihood-ratio tests. Distribution theory for common statistics based on normal distributions.
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Semester: Fall Spring
Prerequisites: MATH/STAT 416 or equivalent. STAT 350 or equivalent is desirable.
Credits: 3
Primary Audience: Actuarial Science, Mathematics, Statistics.
Description: An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Bayes and maximum likelihood estimation. Sufficient statistics. Properties of test of hypotheses. Most powerful and likelihood-ratio tests. Distribution theory for common statistics based on normal distributions.
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STAT 420 Introduction to Time Series (Banner Course Number: 42000)
Semester: Spring
Prerequisites: MA/STAT 416 or equivalent and STAT 350 or equivalent.
Credits: 3
Primary Audience: Actuarial Science, Engineering, and Science students.
Description: Previously taught as STAT 490T. An introduction to time series analysis suitable for actuarial science, engineering, and sciences. Model building and forecasting with ARMA and ARIMA models. Resampling methods for confidence intervals. Multivariate, state-space, and nonlinear models. Volatility models (ARCH and GARCH). Smoothing in time series.
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Semester: Spring
Prerequisites: MA/STAT 416 or equivalent and STAT 350 or equivalent.
Credits: 3
Primary Audience: Actuarial Science, Engineering, and Science students.
Description: Previously taught as STAT 490T. An introduction to time series analysis suitable for actuarial science, engineering, and sciences. Model building and forecasting with ARMA and ARIMA models. Resampling methods for confidence intervals. Multivariate, state-space, and nonlinear models. Volatility models (ARCH and GARCH). Smoothing in time series.
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STAT 472 Actuarial Models (Banner Course Number: 47200)
Semester: Fall
Prerequisites: MA 373 and MA/STAT 416
Credits: 3
Primary Audience: Actuarial Science.
Description: Mathematical foundations of actuarial science emphasizing probability models for life contingencies as the basis for analyzing life insurance and life annuities and determining premiums. This course, together with its sequel, STAT 473, provides most of the background for Course 3 of the Society of Actuaries and the Casualty Actuarial Society.
Taught Fall Semester Only.
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Semester: Fall
Prerequisites: MA 373 and MA/STAT 416
Credits: 3
Primary Audience: Actuarial Science.
Description: Mathematical foundations of actuarial science emphasizing probability models for life contingencies as the basis for analyzing life insurance and life annuities and determining premiums. This course, together with its sequel, STAT 473, provides most of the background for Course 3 of the Society of Actuaries and the Casualty Actuarial Society.
Taught Fall Semester Only.
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STAT 473 Actuarial Models II (Banner Course Number: 47300)
Semester: Spring
Prerequisites: STAT 472.
Credits: 3
Primary Audience: Actuarial Science.
Description: Continuation of STAT 472. Together, these courses cover contingent payment models, survival models, frequency and severity models, compound distribution models, simulation models, stochastic process models and ruin models. Taught Spring Semester Only.
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Semester: Spring
Prerequisites: STAT 472.
Credits: 3
Primary Audience: Actuarial Science.
Description: Continuation of STAT 472. Together, these courses cover contingent payment models, survival models, frequency and severity models, compound distribution models, simulation models, stochastic process models and ruin models. Taught Spring Semester Only.
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STAT 478 Introduction to Bioinformatics (CS 478 and BIOL 478) (Banner Course Number: 47800)
Semester: Fall
Prerequisites: BIOL 231 and 241 or BIOL 295E and CS 180 or equivalent courses are required; also by consent of instructor.
Credits: 3
Primary Audience: Designed for science undergraduate students who have attained at least junior-level standing in their major. Background in biology and computational science are required. Special considerations for students outside these areas will be considered.
Description: The unveiling of the map of the human genome signals the dawning of the post-genomics age. New technologies and information are reapidly converging to change the way we do science and the way science will impact our culture. Some of these developments include the sequencing of the chromosomal content in an entire organism, high through-put strategies to identify genes whose patterns of expression change in response to the needs of the organism, and advances in the visualization of the structures of the proteins that are encoded by the genes.
This inter-disciplinary course is team-taught by faculty from biology, computer sciences, and statistics. The course will focus on genome analysis, protein structural analysis and gene expression profiling (microarray) strategies, and will include a presentation of the context of bioinformatics, the methods of data acquisition, the strategies by which the data are analyzed including the use of appropriate anaysis software, and the ways the data are interpreted.
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Semester: Fall
Prerequisites: BIOL 231 and 241 or BIOL 295E and CS 180 or equivalent courses are required; also by consent of instructor.
Credits: 3
Primary Audience: Designed for science undergraduate students who have attained at least junior-level standing in their major. Background in biology and computational science are required. Special considerations for students outside these areas will be considered.
Description: The unveiling of the map of the human genome signals the dawning of the post-genomics age. New technologies and information are reapidly converging to change the way we do science and the way science will impact our culture. Some of these developments include the sequencing of the chromosomal content in an entire organism, high through-put strategies to identify genes whose patterns of expression change in response to the needs of the organism, and advances in the visualization of the structures of the proteins that are encoded by the genes.
This inter-disciplinary course is team-taught by faculty from biology, computer sciences, and statistics. The course will focus on genome analysis, protein structural analysis and gene expression profiling (microarray) strategies, and will include a presentation of the context of bioinformatics, the methods of data acquisition, the strategies by which the data are analyzed including the use of appropriate anaysis software, and the ways the data are interpreted.
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STAT 479 Loss Models (Banner Course Number: 47900)
Semester: Fall
Prerequisites: STAT 416 and 417
Credits: 3
Primary Audience: Actuarial Science students
Description: This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models.
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Semester: Fall
Prerequisites: STAT 416 and 417
Credits: 3
Primary Audience: Actuarial Science students
Description: This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models.
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STAT 490 Topics in Statistics for Undergraduates (Banner Course Number: 49000)
Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: Supervised reading course or special topics course at the senior level for undergraduates. Requires consent of instructor.
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Semester: Fall Spring Summer
Prerequisites:
Credits: 1-5
Primary Audience:
Description: Supervised reading course or special topics course at the senior level for undergraduates. Requires consent of instructor.
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STAT 490C.F08 Loss Models (Banner Course Number: 49000)
Semester: Fall
Prerequisites: A thorough knowledge of calculus, probability and mathematical statistics is assumed.
Credits: 3
Primary Audience: Actuarial Science students
Description: This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models.
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Semester: Fall
Prerequisites: A thorough knowledge of calculus, probability and mathematical statistics is assumed.
Credits: 3
Primary Audience: Actuarial Science students
Description: This material provides an introduction to modeling and covers important actuarial methods that are useful in modeling. Students will be introduced to survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. The student will further learn to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. The student will be introduced to a variety of tools for the calibration and evaluation of the models.
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STAT 490M Introduction to Computing With Data (Banner Course Number: 49000)
Semester: Fall
Prerequisites: None.
Credits: 3
Primary Audience: The course is intended for sophomores, juniors, and seniors from all disciplines who are interested in computing with data.
Description: Professionals in many disciplines share a need to investigate and present data using the computer. Data visualizations can be convincing or enlightening; they can also be deliberately misleading. In this course, we will learn critical thinking skills for data analysis and visualization. We will also gain practical experience in effectively analyzing and presenting data. The course will include lectures and reading material on data analysis, from experts in several disciplines.
We will gain an understanding of many computational tools for manipulating and interpreting data. The course will begin with projects about data storage and transformation. We will learn how to extract the relevant portions of large data sets. We will display and visualize data to gain insight and understanding. Examples of data to be considered might include online maps and satellite imagery; genetic sequences; election results; literary texts; airline scheduling; social and environmental data.
We will have a multidisciplinary perspective throughout the course. In particular, we will learn how data is analyzed, interpreted, and presented effectively in different disciplines. Experts from various areas will be invited to share their insights, perspectives, and experience in data analysis.
The projects in the course will be geared towards hands-on techniques and tools for computing with data. The key goal is to enable students with practical skills for analyzing and displaying data effectively using the computer.
No prior computational or statistical experience is necessary. The skills learned in this course will be useful to students from nearly every discipline.
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Semester: Fall
Prerequisites: None.
Credits: 3
Primary Audience: The course is intended for sophomores, juniors, and seniors from all disciplines who are interested in computing with data.
Description: Professionals in many disciplines share a need to investigate and present data using the computer. Data visualizations can be convincing or enlightening; they can also be deliberately misleading. In this course, we will learn critical thinking skills for data analysis and visualization. We will also gain practical experience in effectively analyzing and presenting data. The course will include lectures and reading material on data analysis, from experts in several disciplines.
We will gain an understanding of many computational tools for manipulating and interpreting data. The course will begin with projects about data storage and transformation. We will learn how to extract the relevant portions of large data sets. We will display and visualize data to gain insight and understanding. Examples of data to be considered might include online maps and satellite imagery; genetic sequences; election results; literary texts; airline scheduling; social and environmental data.
We will have a multidisciplinary perspective throughout the course. In particular, we will learn how data is analyzed, interpreted, and presented effectively in different disciplines. Experts from various areas will be invited to share their insights, perspectives, and experience in data analysis.
The projects in the course will be geared towards hands-on techniques and tools for computing with data. The key goal is to enable students with practical skills for analyzing and displaying data effectively using the computer.
No prior computational or statistical experience is necessary. The skills learned in this course will be useful to students from nearly every discipline.
Schedule and Textbook Information for Fall 2009
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Course Page for Fall 2009
