Social Statistics (ILRST)Industrial and Labor Relations

Showing 7 results.

Course descriptions provided by the 2025-2026 Catalog.

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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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: STSCI 2100

  • 4 Credits GradeNoAud

  •  5617 ILRST 2100   LEC 001

    • TR
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

    Beginning with the first day of classes Industrial and Labor Relations (ILR) students must get permission to drop from an advisor in the ILR Office of Student Services.

  •  5625 ILRST 2100   DIS 201

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5626 ILRST 2100   DIS 202

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5627 ILRST 2100   DIS 203

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5628 ILRST 2100   DIS 204

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5629 ILRST 2100   DIS 205

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5630 ILRST 2100   DIS 206

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5631 ILRST 2100   DIS 208

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5632 ILRST 2100   DIS 209

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5633 ILRST 2100   DIS 210

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5711 ILRST 2100   DIS 212

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5712 ILRST 2100   DIS 214

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5743 ILRST 2100   DIS 216

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5744 ILRST 2100   DIS 217

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5752 ILRST 2100   DIS 218

    • R
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5745 ILRST 2100   DIS 219

    • R
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5703 ILRST 2100   DIS 220

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5704 ILRST 2100   DIS 221

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5705 ILRST 2100   DIS 222

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5706 ILRST 2100   DIS 223

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5707 ILRST 2100   DIS 224

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

  •  5708 ILRST 2100   DIS 225

    • F
    • Jan 20 - May 5, 2026
    • Entner, J

  • Instruction Mode: In Person

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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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ILRST 5110STSCI 2110STSCI 5110

  • 4 Credits GradeNoAud

  •  5647 ILRST 2110   LEC 001

    • TR
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  5648 ILRST 2110   DIS 201

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  5649 ILRST 2110   DIS 202

    • R
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  7058 ILRST 2110   DIS 203

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  7059 ILRST 2110   DIS 204

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

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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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 3080STSCI 3080STSCI 5080

  • 4 Credits Stdnt Opt

  •  5740 ILRST 3080   LEC 001

    • MW
    • Jan 20 - May 5, 2026
    • Bunea, F

  • Instruction Mode: In Person

  •  5741 ILRST 3080   DIS 201

    • T
    • Jan 20 - May 5, 2026
    • Bunea, F

  • Instruction Mode: In Person

  •  5742 ILRST 3080   DIS 202

    • R
    • Jan 20 - May 5, 2026
    • Bunea, F

  • Instruction Mode: In Person

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

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ECON 3110STSCI 3110

  • 4 Credits Graded

  • 18034 ILRST 3110   LEC 001

    • MW
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  • 18035 ILRST 3110   DIS 201

    • R
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  • 18036 ILRST 3110   DIS 202

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  • 18037 ILRST 3110   DIS 203

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  • 18038 ILRST 3110   DIS 204

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

ILRST 4100

This course is on the basics of multivariate statistical analysis. The focus ison the applied side, and the students will learn by examples of multiple real-life datasets. Studentswill learn to visualize ... view course details

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Syllabi: none
  •   Regular Academic Session.  Combined with: BTRY 4100STSCI 4100STSCI 5111

  • 4 Credits Stdnt Opt

  •  5780 ILRST 4100   LEC 001

    • MW
    • Jan 20 - May 5, 2026
    • Yang, D

  • Instruction Mode: In Person

ILRST 4550

Introduces statistical tools for the analysis of time-dependent data. Data analysis and application will be an integral part of this course. Topics include linear, nonlinear, seasonal, multivariate modeling, ... view course details

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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ORIE 5550STSCI 4550STSCI 5550

  • 4 Credits Opt NoAud

  •  5753 ILRST 4550   LEC 001

    • TR
    • Jan 20 - May 5, 2026
    • Kim, Y

  • Instruction Mode: In Person

    Prerequisite: STSCI 3080 or MATH 4710, STSCI 4030 or equivalent or permission of instructor.

  •  5754 ILRST 4550   DIS 201

    • F
    • Jan 20 - May 5, 2026
    • Kim, Y

  • Instruction Mode: In Person

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

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ILRST 2110STSCI 2110STSCI 5110

  • 4 Credits GradeNoAud

  •  5618 ILRST 5110   LEC 001

    • TR
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  5642 ILRST 5110   DIS 201

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  5643 ILRST 5110   DIS 202

    • R
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  7062 ILRST 5110   DIS 203

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person

  •  7063 ILRST 5110   DIS 204

    • F
    • Jan 20 - May 5, 2026
    • Packard, K

  • Instruction Mode: In Person