school_admissions: High School Admissions Data
In gorica: Evaluation of Inequality Constrained Hypotheses Using GORICA
school_admissions R Documentation
High School Admissions Data
Description
This dataset, provided by the UCLA Statistical Consulting Group (2021),
contains information on factors that influence whether or not a high school
senior is admitted into a very competitive engineering school. The dataset
includes the following variables:
Usage
data(school_admissions)
Format
A data frame with 30 rows and 3 variables.
Details
female binary Binary variable indicating the gender of the student.
apcalc binary Binary variable indicating whether or not the student took Advanced Placement calculus in high school.
admit binary Binary outcome variable indicating admission status, where 1 represents admission and 0 represents non-admission.
The dataset is used for exact logistic regression analysis due to the binary outcome variable. It aims to identify the factors that contribute to admission decisions in a highly competitive engineering school. Since the dataset has a small sample size, specialized procedures are required for accurate estimation.
References
Introduction to SAS. UCLA: Statistical Consulting Group. from
https://stats.oarc.ucla.edu/sas/modules/introduction-to-the-features-of-sas/
(accessed August 22, 2021).
gorica documentation built on Oct. 11, 2023, 9:07 a.m.
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| school_admissions | R Documentation |
High School Admissions Data
Description
This dataset, provided by the UCLA Statistical Consulting Group (2021), contains information on factors that influence whether or not a high school senior is admitted into a very competitive engineering school. The dataset includes the following variables:
Usage
data(school_admissions)
Format
A data frame with 30 rows and 3 variables.
Details
| female | binary | Binary variable indicating the gender of the student. |
| apcalc | binary | Binary variable indicating whether or not the student took Advanced Placement calculus in high school. |
| admit | binary | Binary outcome variable indicating admission status, where 1 represents admission and 0 represents non-admission. |
The dataset is used for exact logistic regression analysis due to the binary outcome variable. It aims to identify the factors that contribute to admission decisions in a highly competitive engineering school. Since the dataset has a small sample size, specialized procedures are required for accurate estimation.
References
Introduction to SAS. UCLA: Statistical Consulting Group. from https://stats.oarc.ucla.edu/sas/modules/introduction-to-the-features-of-sas/ (accessed August 22, 2021).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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