Social Statistics (ILRST)Industrial and Labor Relations

Showing 10 results.

Course descriptions provided by the Courses of Study 2023-2024. Courses of Study 2023-2024 is scheduled to publish mid-June.

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

  •  8873 ILRST 2100   LEC 001

    • TR Ives Hall 305
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8880 ILRST 2100   DIS 201

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8881 ILRST 2100   DIS 202

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8882 ILRST 2100   DIS 203

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8883 ILRST 2100   DIS 204

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8884 ILRST 2100   DIS 205

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  9148 ILRST 2100   DIS 206

    • F Ives Hall 103
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8885 ILRST 2100   DIS 207

    • F Ives Hall 107
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8886 ILRST 2100   DIS 208

    • F Ives Hall 107
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8887 ILRST 2100   DIS 209

    • F Ives Hall 107
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8888 ILRST 2100   DIS 210

    • F Ives Hall 107
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  8889 ILRST 2100   DIS 211

    • F Ives Hall 109
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  9074 ILRST 2100   DIS 212

    • F Ives Hall 107
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  9082 ILRST 2100   DIS 213

    • F Ives Hall 215
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  9085 ILRST 2100   DIS 214

    • R Ives Hall 109
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

  •  9086 ILRST 2100   DIS 215

    • R Ives Hall 109
    • Aug 21 - Dec 4, 2023
    • Packard, K

  • Instruction Mode: In Person

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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Syllabi: none
  •   Seven Week - First.  Choose one lecture and one project. Combined with: STSCI 2130

  • 2 Credits GradeNoAud

  • 12282 ILRST 2130   LEC 001

    • MW Ives Hall 111
    • Aug 21 - Oct 6, 2023
    • Das, S

  • Instruction Mode: In Person
    Introductory Statistics or Instructor Approval.

  • 19323 ILRST 2130   PRJ 601

    • TBA
    • Aug 21 - Oct 6, 2023
    • Das, S

  • 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 3080

  • 4 Credits Stdnt Opt

  •  9092 ILRST 3080   LEC 001

  • Instruction Mode: In Person
    Prerequisites: BTRY 3010, Calculus II, Multivariable calculus, or the equivalent.

  •  9093 ILRST 3080   DIS 201

  • Instruction Mode: In Person

  •  9094 ILRST 3080   DIS 202

  • Instruction Mode: In Person

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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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one project. Combined with: BTRY 3100STSCI 3100STSCI 5100

  • 4 Credits Stdnt Opt

  •  9049 ILRST 3100   LEC 001

    • MW Caldwell Hall 100
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person
    Prerequisite: two semesters of statistics.

  • 19361 ILRST 3100   PRJ 601

    • TBA
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • 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

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

  • 4 Credits Graded

  •  9075 ILRST 3110   LEC 001

    • MW Ives Hall 105
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person
    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.

  •  9076 ILRST 3110   DIS 201

    • F Ives Hall 115
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person

  •  9138 ILRST 3110   DIS 202

    • F Ives Hall 115
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person

  •  9150 ILRST 3110   DIS 203

    • F Ives Hall 115
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person

  •  9149 ILRST 3110   DIS 204

    • F Ives Hall 111
    • Aug 21 - Dec 4, 2023
    • Diciccio, T

  • Instruction Mode: In Person

ILRST 3900

Causal claims are essential in both science and policy. Would a new experimental drug improve disease survival? Would a new advertisement cause higher sales? Would a person's income be higher if they finished ... view course details

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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: INFO 3900STSCI 3900

  • 3 Credits Stdnt Opt

  • 19894 ILRST 3900   LEC 001

    • TR Warren Hall 175
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

      Wang, Y

  • Instruction Mode: In Person
    Causal claims are essential in both science and policy. Would a new experimental drug improve disease survival? Would a new advertisement cause higher sales? Would a person’s income be higher if they finished college? These questions involve counterfactuals: outcomes that would be realized if a treatment were assigned differently. This course will define counterfactuals mathematically, formalize conceptual assumptions that link empirical evidence to causal conclusions, and engage with statistical methods for estimation. Students will enter the course with knowledge of statistical inference: how to assess if a variable is associated with an outcome. Students will emerge from the course with knowledge of causal inference: how to assess whether an intervention to change that input would lead to a change in the outcome.

  • 19895 ILRST 3900   DIS 201

    • W Olin Hall 145
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

      Wang, Y

  • Instruction Mode: In Person

  • 19896 ILRST 3900   DIS 202

    • W Upson Hall 146
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

      Wang, Y

  • Instruction Mode: In Person

  • 19897 ILRST 3900   DIS 203

    • W Upson Hall 152
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

      Wang, Y

  • Instruction Mode: In Person

  • 19898 ILRST 3900   DIS 204

    • W Warren Hall 137
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

  • Instruction Mode: In Person

  • 19899 ILRST 3900   DIS 205

    • W Upson Hall 152
    • Aug 21 - Dec 4, 2023
    • Lundberg, I

      Wang, Y

  • Instruction Mode: In Person

ILRST 4110

Categorical data analysis, including logistic regression, log-linear models, stratified tables, matched pairs analysis, polytomous response, and ordinal data. Applications in biological, biomedical and ... view course details

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Syllabi: none
  •   Regular Academic Session.  Combined with: BTRY 4110STSCI 4110STSCI 5160

  • 3 Credits Graded

  •  9168 ILRST 4110   LEC 001

    • TR Ives Hall 115
    • Aug 21 - Dec 4, 2023
    • Smith, M

  • Instruction Mode: In Person

ILRST 5050

This course introduces MILR students to the critical analysis process involved in social science research and practice in the workplace. The uses of analytics, particularly in workforce development will ... view course details

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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 4 Credits GradeNoAud

  •  9140 ILRST 5050   LEC 001

    • MW Ives Hall 105
    • Aug 21 - Dec 4, 2023
    • Karns, M

  • Instruction Mode: In Person

  •  9141 ILRST 5050   DIS 211

    • W Ives Hall 109
    • Aug 21 - Dec 4, 2023
    • Karns, M

  • Instruction Mode: In Person

  •  9142 ILRST 5050   DIS 212

    • R Ives Hall 109
    • Aug 21 - Dec 4, 2023
    • Karns, M

  • Instruction Mode: In Person

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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Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: BTRY 6010

  • 4 Credits Stdnt Opt

  •  8960 ILRST 6100   LEC 001

  • Instruction Mode: In Person
    Enrollment limited to: graduate students or permission of instructor.

  •  8961 ILRST 6100   DIS 202

  • Instruction Mode: In Person

  •  8962 ILRST 6100   DIS 203

  • Instruction Mode: In Person

  •  8963 ILRST 6100   DIS 204

  • Instruction Mode: In Person

  •  9088 ILRST 6100   DIS 205

  • Instruction Mode: In Person

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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Syllabi: none
  •   Regular Academic Session.  Combined with: ORIE 7170STSCI 7170

  • 3 Credits Stdnt Opt

  •  9087 ILRST 7170   LEC 001

  • Instruction Mode: In Person