Spring 2025 | SOC 8811 Section 001: Advanced Social Statistics (51413)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session01/21/2025 - 05/05/2025Tue, Thu 02:30PM - 03:45PMUMTC, West Bank
- Enrollment Status:
- Open (0 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed course information: http://classinfo.umn.edu/?tvanheuv+SOC8811+Spring2025
- Class Description:
Many of the questions that we wish to answer in the social sciences address outcomes that are limited and fixed in their answer choices. For example, do Americans agree that Atheists share a common vision of American society? How did the Great Recession affect employment inequalities across racial groups? Who do happy people compare themselves to? Which social class does the child of a blue-collar worker end up in? How frequently do adolescents use marijuana? Questions such as these cannot be appropriately answered using linear regression models, requiring more advanced techniques which will be covered extensively in Soc8811.
This course will focus on applied statistics and primarily deal with regression models in which the dependent variable is categorical: binary, nominal, ordinal, count, etc. As a catalyst for the course, we will consider flexible methods developed for introducing nonlinearities into the linear regression framework. Specific models to be addressed include: logit, probit, generalized ordered logit, multinomial logit, Poisson, negative binomial, zero inflated, fractional response, LOWESS, kernel weighted local polynomial, and mixture models.
Throughout the course, we will address common statistical issues that require special consideration when applied to nonlinear regression models, including: the calculation of predictions, interpretation of coefficients, interaction, and mediation. We will also become familiarized with techniques developed for applied research: model fit, selection, and robustness, joint hypothesis testing, weighting, clustering, and poststratification for complex survey design, and missing data.
Soc8811 covers statistical methods for analyzing social data and is designed for graduate students in the social sciences. Students are assumed to have a background equivalent to Soc5811 and thus have familiarity with linear regression models. The course will be taught in Stata, but students will have the opportunity to instead use R if they prefer.- Learning Objectives:
1. Produce, interpret, and report results from complex statistical models
2. Understand how to apply data analysis to substantive research questions, and effectively present results to a general interest academic audience
3. Develop strategies and competency to conduct future studies of advanced techniques in quantitative methods
4. Build a robust, reproducible workflow to move from raw data to numerical and visual information placed in a final paper.
- Grading:
- Grading is based on 11 statistical computing assignments
- Class Format:
- In person, lectures, statistical computing lab.
- Workload:
- 11 Statistical Computing AssignmentsReadings include textbook and lecture notes.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/51413/1253
- Instructor Supplied Information Last Updated:
- 10 November 2022
Spring 2024 | SOC 8811 Section 001: Advanced Social Statistics (51697)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session01/16/2024 - 04/29/2024Tue, Thu 02:30PM - 03:45PMUMTC, West BankSocial Sciences Building 1114
- Enrollment Status:
- Open (10 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed course information: http://classinfo.umn.edu/?tvanheuv+SOC8811+Spring2024
- Class Description:
Many of the questions that we wish to answer in the social sciences address outcomes that are limited and fixed in their answer choices. For example, do Americans agree that Atheists share a common vision of American society? How did the Great Recession affect employment inequalities across racial groups? Who do happy people compare themselves to? Which social class does the child of a blue-collar worker end up in? How frequently do adolescents use marijuana? Questions such as these cannot be appropriately answered using linear regression models, requiring more advanced techniques which will be covered extensively in Soc8811.
This course will focus on applied statistics and primarily deal with regression models in which the dependent variable is categorical: binary, nominal, ordinal, count, etc. As a catalyst for the course, we will consider flexible methods developed for introducing nonlinearities into the linear regression framework. Specific models to be addressed include: logit, probit, generalized ordered logit, multinomial logit, Poisson, negative binomial, zero inflated, fractional response, LOWESS, kernel weighted local polynomial, and mixture models.
Throughout the course, we will address common statistical issues that require special consideration when applied to nonlinear regression models, including: the calculation of predictions, interpretation of coefficients, interaction, and mediation. We will also become familiarized with techniques developed for applied research: model fit, selection, and robustness, joint hypothesis testing, weighting, clustering, and poststratification for complex survey design, and missing data.
Soc8811 covers statistical methods for analyzing social data and is designed for graduate students in the social sciences. Students are assumed to have a background equivalent to Soc5811 and thus have familiarity with linear regression models. The course will be taught in Stata, but students will have the opportunity to instead use R if they prefer.- Learning Objectives:
1. Produce, interpret, and report results from complex statistical models
2. Understand how to apply data analysis to substantive research questions, and effectively present results to a general interest academic audience
3. Develop strategies and competency to conduct future studies of advanced techniques in quantitative methods
4. Build a robust, reproducible workflow to move from raw data to numerical and visual information placed in a final paper.
- Grading:
- Grading is based on 11 statistical computing assignments
- Class Format:
- In person, lectures, statistical computing lab.
- Workload:
- 11 Statistical Computing AssignmentsReadings include textbook and lecture notes.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/51697/1243
- Instructor Supplied Information Last Updated:
- 10 November 2022
Spring 2023 | SOC 8811 Section 001: Advanced Social Statistics (52041)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session01/17/2023 - 05/01/2023Tue, Thu 02:30PM - 03:45PMUMTC, West BankSocial Sciences Building 1114
- Enrollment Status:
- Open (8 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed course information: http://classinfo.umn.edu/?tvanheuv+SOC8811+Spring2023
- Class Description:
Many of the questions that we wish to answer in the social sciences address outcomes that are limited and fixed in their answer choices. For example, do Americans agree that Atheists share a common vision of American society? How did the Great Recession affect employment inequalities across racial groups? Who do happy people compare themselves to? Which social class does the child of a blue-collar worker end up in? How frequently do adolescents use marijuana? Questions such as these cannot be appropriately answered using linear regression models, requiring more advanced techniques which will be covered extensively in Soc8811.
This course will focus on applied statistics and primarily deal with regression models in which the dependent variable is categorical: binary, nominal, ordinal, count, etc. As a catalyst for the course, we will consider flexible methods developed for introducing nonlinearities into the linear regression framework. Specific models to be addressed include: logit, probit, generalized ordered logit, multinomial logit, Poisson, negative binomial, zero inflated, fractional response, LOWESS, kernel weighted local polynomial, and mixture models.
Throughout the course, we will address common statistical issues that require special consideration when applied to nonlinear regression models, including: the calculation of predictions, interpretation of coefficients, interaction, and mediation. We will also become familiarized with techniques developed for applied research: model fit, selection, and robustness, joint hypothesis testing, weighting, clustering, and poststratification for complex survey design, and missing data.
Soc8811 covers statistical methods for analyzing social data and is designed for graduate students in the social sciences. Students are assumed to have a background equivalent to Soc5811 and thus have familiarity with linear regression models. The course will be taught in Stata, but students will have the opportunity to instead use R if they prefer.- Learning Objectives:
1. Produce, interpret, and report results from complex statistical models
2. Understand how to apply data analysis to substantive research questions, and effectively present results to a general interest academic audience
3. Develop strategies and competency to conduct future studies of advanced techniques in quantitative methods
4. Build a robust, reproducible workflow to move from raw data to numerical and visual information placed in a final paper.
- Grading:
- Grading is based on 11 statistical computing assignments
- Class Format:
- In person, lectures, statistical computing lab.
- Workload:
- 11 Statistical Computing AssignmentsReadings include textbook and lecture notes.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/52041/1233
- Instructor Supplied Information Last Updated:
- 10 November 2022
Spring 2022 | SOC 8811 Section 001: Advanced Social Statistics (52848)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session01/18/2022 - 05/02/2022Tue, Thu 02:30PM - 03:45PMUMTC, West BankBlegen Hall 210
- Enrollment Status:
- Open (5 of 12 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed course information: http://classinfo.umn.edu/?knoke001+SOC8811+Spring2022
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, and multilevel modeling or structural equation models.
- Grading:
- 3 data analysis papers on the three topics, each 33.3% of the course grade.
- Exam Format:
- No exams
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Data Analysis Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/52848/1223
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf (Spring 2016)
- Instructor Supplied Information Last Updated:
- 17 September 2018
Spring 2021 | SOC 8811 Section 001: Advanced Social Statistics (48772)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Partially Online
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session01/19/2021 - 05/03/2021Tue, Thu 02:30PM - 03:45PMUMTC, West BankBlegen Hall 11501/19/2021 - 05/03/2021Tue, Thu 02:30PM - 03:45PMUMTC, West BankUMN ONLINE-HYB
- Enrollment Status:
- Closed (12 of 12 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- 6 seats reserved for Sociology grad students. Some students will be physically present for this in person grad class. The rest will be online synchronous at the scheduled class times via zoom. Click this link for more detailed information: http://classinfo.umn.edu/?tvanheuv+SOC8811+Spring2021
- Class Description:
Many of the questions that we wish to answer in the social sciences address outcomes that are limited and fixed in their answer choices. For example, do Americans agree that Atheists share a common vision of American society? How did the Great Recession affect employment inequalities across racial groups? Who do happy people compare themselves to? Which social class does the child of a blue-collar worker end up in? How frequently do adolescents use marijuana? Questions such as these cannot be appropriately answered using linear regression models, requiring more advanced techniques which will be covered extensively in Soc8811.
This course will focus on applied statistics and primarily deal with regression models in which the dependent variable is categorical: binary, nominal, ordinal, count, etc. As a catalyst for the course, we will consider flexible methods developed for introducing nonlinearities into the linear regression framework. Specific models to be addressed include: logit, probit, generalized ordered logit, multinomial logit, Poisson, negative binomial, zero inflated, fractional response, LOWESS, kernel weighted local polynomial, and mixture models.
Throughout the course, we will address common statistical issues that require special consideration when applied to nonlinear regression models, including: the calculation of predictions, interpretation of coefficients, interaction, and mediation. We will also become familiarized with techniques developed for applied research: model fit, selection, and robustness, joint hypothesis testing, weighting, clustering, and poststratification for complex survey design, and missing data.
Soc8811 covers statistical methods for analyzing social data and is designed for graduate students in the social sciences. Students are assumed to have a background equivalent to Soc5811 and thus have familiarity with linear regression models. The course will be taught in Stata, but students will have the opportunity to instead use R if they prefer.- Learning Objectives:
1. Produce, interpret, and report results from complex statistical models
2. Understand how to apply data analysis to substantive research questions, and effectively present results to a general interest academic audience
3. Develop strategies and competency to conduct future studies of advanced techniques in quantitative methods
4. Build a robust, reproducible workflow to move from raw data to numerical and visual information placed in a final paper.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/48772/1213
- Instructor Supplied Information Last Updated:
- 1 November 2019
Spring 2020 | SOC 8811 Section 001: Advanced Social Statistics (52265)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Regular Academic Session01/21/2020 - 05/04/2020Tue, Thu 02:30PM - 03:45PMUMTC, West BankSocial Sciences Building 1114
- Enrollment Status:
- Closed (16 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed information: http://classinfo.umn.edu/?tvanheuv+SOC8811+Spring2020
- Class Description:
Many of the questions that we wish to answer in the social sciences address outcomes that are limited and fixed in their answer choices. For example, do Americans agree that Atheists share a common vision of American society? How did the Great Recession affect employment inequalities across racial groups? Who do happy people compare themselves to? Which social class does the child of a blue-collar worker end up in? How frequently do adolescents use marijuana? Questions such as these cannot be appropriately answered using linear regression models, requiring more advanced techniques which will be covered extensively in Soc8811.
This course will focus on applied statistics and primarily deal with regression models in which the dependent variable is categorical: binary, nominal, ordinal, count, etc. As a catalyst for the course, we will consider flexible methods developed for introducing nonlinearities into the linear regression framework. Specific models to be addressed include: logit, probit, generalized ordered logit, multinomial logit, Poisson, negative binomial, zero inflated, fractional response, LOWESS, kernel weighted local polynomial, and mixture models.
Throughout the course, we will address common statistical issues that require special consideration when applied to nonlinear regression models, including: the calculation of predictions, interpretation of coefficients, interaction, and mediation. We will also become familiarized with techniques developed for applied research: model fit, selection, and robustness, joint hypothesis testing, weighting, clustering, and poststratification for complex survey design, and missing data.
Soc8811 covers statistical methods for analyzing social data and is designed for graduate students in the social sciences. Students are assumed to have a background equivalent to Soc5811 and thus have familiarity with linear regression models. The course will be taught in Stata, but students will have the opportunity to instead use R if they prefer.- Learning Objectives:
1. Produce, interpret, and report results from complex statistical models
2. Understand how to apply data analysis to substantive research questions, and effectively present results to a general interest academic audience
3. Develop strategies and competency to conduct future studies of advanced techniques in quantitative methods
4. Build a robust, reproducible workflow to move from raw data to numerical and visual information placed in a final paper.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/52265/1203
- Instructor Supplied Information Last Updated:
- 1 November 2019
Spring 2019 | SOC 8811 Section 001: Advanced Social Statistics (52399)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Regular Academic Session01/22/2019 - 05/06/2019Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Enrollment Status:
- Open (10 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed information: http://classinfo.umn.edu/?knoke001+SOC8811+Spring2019
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, and multilevel modeling or structural equation models.
- Grading:
- 3 data analysis papers on the three topics, each 33.3% of the course grade.
- Exam Format:
- No exams
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Data Analysis Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/52399/1193
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf (Spring 2016)
- Instructor Supplied Information Last Updated:
- 17 September 2018
Spring 2018 | SOC 8811 Section 001: Advanced Social Statistics (49141)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Regular Academic Session01/16/2018 - 05/04/2018Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Enrollment Status:
- Open (12 of 15 seats filled)
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed information: http://classinfo.umn.edu/?knoke001+SOC8811+Spring2018
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, structural equation models.
- Grading:
- 3 data analysis papers on the three topics, each 33.3% of the course grade.
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/49141/1183
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf (Spring 2016)
- Instructor Supplied Information Last Updated:
- 12 October 2015
Spring 2017 | SOC 8811 Section 001: Advanced Social Statistics (49563)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Regular Academic Session01/17/2017 - 05/05/2017Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: recommend 5811 or equiv; graduate student or instr consent
- Class Notes:
- Click this link for more detailed information: http://classinfo.umn.edu/?knoke001+SOC8811+Spring2017
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, structural equation models.
- Grading:
- 3 data analysis papers on the three topics, each 33.3% of the course grade.
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/49563/1173
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf (Spring 2016)
- Instructor Supplied Information Last Updated:
- 12 October 2015
Spring 2016 | SOC 8811 Section 001: Advanced Social Statistics (47551)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Regular Academic Session01/19/2016 - 05/06/2016Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: 5811 or equiv, grad soc major or instr consent
- Class Notes:
- Click this link for more detailed information http://classinfo.umn.edu/?knoke001+SOC8811+Spring2016
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, structural equation models.
- Grading:
- 3 data analysis papers on the three topics, each 33.3% of the course grade.
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/47551/1163
- Syllabus:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf
- Instructor Supplied Information Last Updated:
- 12 October 2015
Spring 2015 | SOC 8811 Section 001: Advanced Social Statistics (47392)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Class Attributes:
- Delivery Medium
- Times and Locations:
- Regular Academic Session01/20/2015 - 05/08/2015Mon, Wed 01:00PM - 02:15PMUMTC, West BankSocial Sciences Building 1114
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers. prereq: 5811 or equiv, grad soc major or instr consent
- Class Description:
- Statistical methods for analyzing social data. This course is designed for Sociology graduate students and assumes a background equivalent to Soc 5811 Intermediate Social Statistics. The class will be comprised primarily of introduction to modern statistical techniques such as categorical data analysis (e.g., logistic regression), time series analysis (e.g., event history analysis), and modern computational statistics (e.g., monte carlo tests). Labs are organized to help students with the data analysis required to complete the weekly exercises, develop the term paper, and to further training in statistical software used by social science researchers.
- Grading:
- Other Grading Information: weekly/bi-weekly assignments, 1 take-home exam, 1 research paper.
- Class Format:
- 70% Lecture
30% Laboratory - Workload:
- 5-15 Pages Reading Per Week Other Workload: weekly/bi-weekly assignments, 1 take-home exam, 1 research paper.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/47392/1153
- Instructor Supplied Information Last Updated:
- 18 April 2013
Spring 2014 | SOC 8811 Section 001: Advanced Social Statistics (52128)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Class Attributes:
- Delivery Medium
- Times and Locations:
- Regular Academic Session01/21/2014 - 05/09/2014Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers.
- Class Description:
- Statistical methods for analyzing social data. This course is designed for Sociology graduate students and assumes a background equivalent to Soc 5811 Intermediate Social Statistics. The class will be comprised primarily of introduction to modern statistical techniques such as categorical data analysis (e.g., logistic regression), time series analysis (e.g., event history analysis), and modern computational statistics (e.g., monte carlo tests). Labs are organized to help students with the data analysis required to complete the weekly exercises, develop the term paper, and to further training in statistical software used by social science researchers.
- Grading:
- Other Grading Information: weekly/bi-weekly assignments, 1 take-home exam, 1 research paper.
- Class Format:
- 70% Lecture
30% Laboratory - Workload:
- 5-15 Pages Reading Per Week Other Workload: weekly/bi-weekly assignments, 1 take-home exam, 1 research paper.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/52128/1143
- Instructor Supplied Information Last Updated:
- 18 April 2013
Spring 2013 | SOC 8811 Section 001: Advanced Social Statistics (47131)
- Instructor(s)
- Class Component:
- Lecture
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Class Attributes:
- Delivery Medium
- Times and Locations:
- Regular Academic Session01/22/2013 - 05/10/2013Tue, Thu 11:15AM - 12:30PMUMTC, West BankSocial Sciences Building 1114
- Also Offered:
- Course Catalog Description:
- Statistical methods for analyzing social data. Sample topics: advanced multiple regression, logistic regression, limited dependent variable analysis, analysis of variance and covariance, log-linear models, structural equations, and event history analysis. Applications to datasets using computers.
- Class Description:
- Statistical methods for analyzing social data. Topics for Spring 2012: logistic regression, event history analysis, structural equation models.
- Grading:
- 100% Reports/Papers
- Class Format:
- 60% Lecture
10% Discussion
30% Laboratory - Workload:
- 12 Pages Reading Per Week
40 Pages Writing Per Term
3 Paper(s) - Textbooks:
- https://bookstores.umn.edu/course-lookup/47131/1133
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/knoke001_SOC8811_Spring2016.pdf (Spring 2016)
- Instructor Supplied Information Last Updated:
- 7 November 2011
ClassInfo Links - Sociology Classes
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