Social Statistics (ILRST)Industrial and Labor Relations

Showing 10 results.

Course descriptions provided by the Courses of Study 2016-2017.

ILRST 2100

Statistics is about understanding the world through data. We are surrounded by data, so there is a lot to understand. Covers data exploration and display, data gathering methods, probability, and statistical ... view course details

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  • Enrollment Information
    Choose one lecture and one discussion. Combined with: STSCI 2100

  • 4 Credits GradeNoAud

  • 14962ILRST 2100  LEC 001

  • Non-ILR students please enroll in STSCI 2100.

ILRST 2110

A second course in statistics that emphasizes applications to the social sciences. Topics include simple linear regression, multiple linear regression (theory, model building, and model diagnostics), and ... view course details

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  • Enrollment Information
    Choose one lecture and one discussion. Combined with: ILRST 5110STSCI 2110STSCI 5110

  • 3 Credits GradeNoAud

ILRST 2130

This seven week, two-credit class will cover the regression requirements, hypothesis tests, and interpretation of results. Students will learn to identify the data necessary to perform a regression analysis, ... view course details

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    Seven Week - Second. 

  • 2 Credits GradeNoAud

  • 15546ILRST 2130  LEC 001

    • TR
    • Oct 10 - Dec 2, 2016
    • Wells, M

  • Introductory Statistics or Instructor Approval.

ILRST 3080

This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based ... view course details

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    Choose one lecture and one discussion. Combined with: BTRY 3080STSCI 3080

  • 4 Credits Stdnt Opt

ILRST 3100

Theory and application of statistical sampling, especially in regard to sample design, cost, estimation of population quantities, and error estimation. Assessment of nonsampling errors. Discussion ... view course details

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    Combined with: BTRY 3100STSCI 3100

  • 4 Credits Graded

ILRST 3110

This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based ... view course details

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  • Enrollment Information
    Choose one lecture and one discussion. Combined with: ECON 3110STSCI 3110

  • 4 Credits GradeNoAud

  • 15221ILRST 3110  LEC 001

  • Prerequisites: MATH 1110 or equivalent. FORBIDDEN OVERLAP: Students may receive credit for only one course in the following group: ILRST/ECON/STSCI 3110, BTRY/STSCI 3080, ECON 3130, and MATH 4710.

ILRST 5100

A first course in statistics for graduate students in the social sciences. Descriptive statistics, probability and sampling distributions, estimation, hypothesis testing, simple linear regression, and ... view course details

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  • Enrollment Information
    Choose one lecture and one discussion.

  • 3 Credits GradeNoAud

ILRST 5110

Second course in statistics that emphasizes applications to the social sciences. Topics include simple linear regression, multiple linear regression (theory, model building, and model diagnostics), and ... view course details

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  • Enrollment Information
    Choose one lecture and one discussion. Combined with: ILRST 2110STSCI 2110STSCI 5110

  • 3 Credits GradeNoAud

ILRST 6100

Develops and uses statistical methods to analyze data arising from a wide variety of applications. Topics include descriptive statistics, point and interval estimation, hypothesis testing, inference for ... view course details

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    Choose one lecture and one laboratory. Combined with: BTRY 6010

  • 4 Credits Stdnt Opt

  • 15068ILRST 6100  LEC 001

  • Enrollment limited to: graduate students or permission of instructor.

ILRST 7170

Properties of the multivariate normal distribution. Distribution theory for quadratic forms. Properties of least squares and maximum likelihood estimates. Methods for fixed-effect models of less than full ... view course details

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    Combined with: ORIE 7170STSCI 7170

  • 3 Credits Graded