Title: | A Comprehensive Collection of Educational Datasets |
---|---|
Description: | Provides a comprehensive collection of datasets related to education, covering topics such as student performance, learning methods, test scores, absenteeism, and other educational metrics. This package serves as a resource for educational researchers, data analysts, and statisticians to explore and analyze data in the field of education. |
Authors: | Renzo Caceres Rossi [aut, cre] |
Maintainer: | Renzo Caceres Rossi <[email protected]> |
License: | GPL-3 |
Version: | 0.1.0 |
Built: | 2024-12-06 01:36:10 UTC |
Source: | CRAN |
This dataset, ability_list, is a list containing information about six ability and intelligence tests administered to 112 individuals. The dataset provides a covariance matrix, the means (centers) of the variables, and the number of observations.
data(ability_list)
data(ability_list)
A list with 3 components:
A covariance matrix (numeric matrix) of dimensions 6x6, representing the relationships between six different tests.
A numeric vector of length 6 containing the mean scores for each of the six tests.
The total number of observations (integer), which is 112.
The dataset name has been kept as 'ability_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is a list object. The original content has not been modified in any way.
Generated for educational purposes.
This dataset, absenteeism_tbl_df, is a tibble containing information about absenteeism from school and certain demographic characteristics of children in rural New South Wales, Australia. The dataset includes data from 146 randomly sampled students during a particular school year, providing insights into the relationships between absenteeism and variables such as ethnicity, sex, age group, and learning categories.
data(absenteeism_tbl_df)
data(absenteeism_tbl_df)
A tibble with 146 observations and 5 variables:
Ethnicity of the student (factor with 2 levels).
Sex of the student (factor with 2 levels).
Age group of the student (factor with 4 levels).
Learning category of the student, e.g., slow learner or not (factor with 2 levels).
Number of days the student was absent from school (integer).
The dataset name has been kept as 'absenteeism_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
Data collected from a study in rural New South Wales, Australia.
This dataset, Achieve_tbl_df, is a tibble containing information about math achievement test scores for 25 high school students, categorized by gender. The dataset provides insights into the distribution of scores between male and female students.
data(Achieve_tbl_df)
data(Achieve_tbl_df)
A tibble with 25 observations and 2 variables:
Math achievement test score of the student (integer).
Gender of the student (factor with 2 levels: "Male", "Female").
The dataset name has been kept as 'Achieve_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Anxiety_tbl_df, is a tibble containing information about math test scores and anxiety levels before the test for 20 students. The dataset provides insights into the relationship between anxiety levels and math test performance.
data(Anxiety_tbl_df)
data(Anxiety_tbl_df)
A tibble with 20 observations and 2 variables:
Anxiety score of the student before taking the math test (integer).
Math test score of the student (integer).
The dataset name has been kept as 'Anxiety_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Bigten_tbl_df, is a tibble containing information about the graduation rates of student athletes and nonathletes in the Big Ten Conference. The dataset includes data from two academic years, showing the graduation rates by school and athlete status (athletes vs nonathletes).
data(Bigten_tbl_df)
data(Bigten_tbl_df)
A tibble with 44 observations and 4 variables:
Name of the school (character).
Year of the data (factor with 2 levels).
Graduation rate percentage (integer).
Athlete status (character, either 'Athlete' or 'Nonathlete').
The dataset name has been kept as 'Bigten_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
NCAA Graduation Rates Report, 2000.
This dataset, Biology_tbl_df, is a tibble containing the test scores of 30 students on their first exam in a biology class. The dataset provides insight into the distribution of scores among the students.
data(Biology_tbl_df)
data(Biology_tbl_df)
A tibble with 30 observations and 1 variable:
Test scores on the first biology exam (integer).
The dataset name has been kept as 'Biology_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Blackedu_tbl_df, is a tibble containing information about the education level of Black individuals, categorized by gender. The dataset includes 3800 observations and provides insights into the distribution of education levels across different gender groups.
data(Blackedu_tbl_df)
data(Blackedu_tbl_df)
A tibble with 3800 observations and 2 variables:
Gender of the individual (factor with 2 levels).
Education level of the individual (factor with 5 levels).
The dataset name has been kept as 'Blackedu_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
Bureau of Census data.
This dataset, Books_tbl_df, is a tibble containing information about the number of books read and spelling scores for 17 third-grade students. The dataset provides insights into the relationship between the number of books read and spelling scores in this group of students.
data(Books_tbl_df)
data(Books_tbl_df)
A tibble with 17 observations and 2 variables:
Number of books read by the student (integer).
Spelling score of the student (integer).
The dataset name has been kept as 'Books_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, cchousing_tbl_df, is a tibble containing simulated data on housing prices for students at a community college. The dataset provides the housing prices for 75 students, offering insights into the distribution of housing prices in this educational setting.
data(cchousing_tbl_df)
data(cchousing_tbl_df)
A tibble with 75 observations and 1 variable:
Housing price for the student (numeric).
The dataset name has been kept as 'cchousing_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, credits_tbl_df, is a tibble containing simulated data on the number of college credits taken by students each semester. The dataset includes data from 100 students, providing insights into the distribution of credits taken by students in a college setting.
data(credits_tbl_df)
data(credits_tbl_df)
A tibble with 100 observations and 1 variable:
Number of college credits taken by the student (integer).
The dataset name has been kept as 'credits_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package (simulated data).
This dataset, crime_degree_tbl_df, is a tibble containing data on crime rates and the percentage of the population without a high school degree in 51 U.S. states. The dataset includes information on the crime rate and the percentage of the population without a high school degree for each state.
data(crime_degree_tbl_df)
data(crime_degree_tbl_df)
A tibble with 51 observations and 3 variables:
State name (character).
Percentage of the population without a high school degree (numeric).
Crime rate (numeric).
The dataset name has been kept as 'crime_degree_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Detroit_tbl_df, is a tibble containing data on the educational levels of a sample of 40 auto workers in Detroit. The dataset includes information on the highest level of education attained by each worker.
data(Detroit_tbl_df)
data(Detroit_tbl_df)
A tibble with 40 observations and 1 variable:
Educational level of the auto worker (integer).
The dataset name has been kept as 'Detroit_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Develop_tbl_df, is a tibble containing demographic data on students enrolled in developmental education programs at 2-year and 4-year colleges. The dataset includes information on the racial background of the students and whether they are enrolled in 2-year or 4-year colleges.
data(Develop_tbl_df)
data(Develop_tbl_df)
A tibble with 5656 observations and 2 variables:
Racial background of the student (factor with 5 levels).
Type of college the student is enrolled in (factor with 2 levels: 2-year or 4-year).
The dataset name has been kept as 'Develop_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from "Research in Development Education" (1994), V. 11, 2.
This dataset, Devmath_tbl_df, is a tibble containing test scores for students who failed developmental mathematics in the fall semester of 1995. The dataset includes the scores of these students as part of a simulated study.
data(Devmath_tbl_df)
data(Devmath_tbl_df)
A tibble with 40 observations and 1 variable:
Test scores of students who failed developmental mathematics (integer).
The dataset name has been kept as 'Devmath_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package. Data provided by Dr. Anita Kitchens.
This dataset, drug_use_tbl_df, is a tibble containing data on the drug use of students and their parents. The dataset summarizes 445 student-parent pairs, with each pair indicating whether the student and/or their parent has used drugs, specifically marijuana.
data(drug_use_tbl_df)
data(drug_use_tbl_df)
A tibble with 445 observations and 2 variables:
Whether the student has used drugs (factor with 2 levels).
Whether the parent has used drugs (factor with 2 levels).
The dataset name has been kept as 'drug_use_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package. Ellis GJ and Stone LH. 1979. Marijuana Use in College: An Evaluation of a Modeling Explanation. Youth and Society 10:323-334.
This dataset, Dyslexia_tbl_df, is a tibble containing data on a group of college students diagnosed with dyslexia. The dataset includes various personal characteristics such as age, gender, handedness, weight, height, and number of children, along with the number of words they were able to read correctly.
data(Dyslexia_tbl_df)
data(Dyslexia_tbl_df)
A tibble with 8 observations and 7 variables:
Number of words read correctly (integer).
Age of the student (integer).
Gender of the student (character).
Handedness of the student (character).
Weight of the student (integer).
Height of the student (integer).
Number of children the student has (integer).
The dataset name has been kept as 'Dyslexia_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This package provides a comprehensive collection of datasets related to education, covering topics such as student performance, learning methods, test scores, absenteeism, and other educational metrics.
educationR: A Comprehensive Collection of Educational Datasets
A Comprehensive Collection of Educational Datasets.
Maintainer: Renzo Cáceres Rossi [email protected]
Useful links:
This dataset, Engineer_tbl_df, is a tibble containing salary data for engineering graduates 10 years after graduation. The dataset includes information on the salary of the graduates and the type of university they graduated from (categorized into three types of universities).
data(Engineer_tbl_df)
data(Engineer_tbl_df)
A tibble with 51 observations and 2 variables:
Salary of the engineering graduate 10 years after graduation (integer).
Type of university the graduate attended (factor with 3 levels).
The dataset name has been kept as 'Engineer_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Entrance_tbl_df, is a tibble containing the college entrance exam scores of 24 high school seniors. The dataset includes information on their exam scores.
data(Entrance_tbl_df)
data(Entrance_tbl_df)
A tibble with 24 observations and 1 variable:
College entrance exam scores (integer).
The dataset name has been kept as 'Entrance_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, exams_tbl_df, is a tibble containing the exam scores of a class of 19 students. The dataset includes information on their performance in a specific exam.
data(exams_tbl_df)
data(exams_tbl_df)
A tibble with 19 observations and 1 variable:
Exam scores of students (integer).
The dataset name has been kept as 'exams_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, fheights_tbl_df, is a tibble containing the heights of 24 female college students, measured in inches. The dataset provides insight into the physical characteristics of a specific demographic group.
data(fheights_tbl_df)
data(fheights_tbl_df)
A tibble with 24 observations and 1 variable:
Heights of female college students, measured in inches (integer).
The dataset name has been kept as 'fheights_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, German_tbl_df, is a tibble containing data on the number of errors made by 20 students when copying a German passage, both before and after participating in an experimental German course. The dataset provides insights into language learning and the effectiveness of the course.
data(German_tbl_df)
data(German_tbl_df)
A tibble with 20 observations and 3 variables:
Identifier for the student (character).
Indicates whether the errors were recorded "before" or "after" the experimental course (character).
Number of errors made by the student when copying the German passage (integer).
The dataset name has been kept as 'German_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, gifted_tbl_df, is a tibble containing data on the analytical skills of 36 young gifted children, along with several factors that may influence these skills. The dataset includes measures such as parental IQ, early developmental milestones, and television habits.
data(gifted_tbl_df)
data(gifted_tbl_df)
A tibble with 36 observations and 8 variables:
Analytical skills score of the child (integer).
IQ of the father (integer).
IQ of the mother (integer).
Age in months when the child first said "mummy" or "daddy" (integer).
Age in months when the child first counted to 10 successfully (integer).
Average number of hours per week the child's parents read to the child (numeric).
Average number of hours per week the child watched educational TV programs in the past three months (numeric).
Average number of hours per week the child watched cartoons on TV in the past three months (numeric).
The dataset name has been kept as 'gifted_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package. Graybill, F.A. & Iyer, H.K., (1994) *Regression Analysis: Concepts and Applications*, Duxbury, p. 511-6.
This dataset, GPA_college_tbl_df, is a tibble containing data on the relationship between high school GPA and college GPA for 10 students. The dataset is valuable for analyzing academic performance correlations across different educational levels.
data(GPA_college_tbl_df)
data(GPA_college_tbl_df)
A tibble with 10 observations and 2 variables:
High school GPA (numeric).
College GPA (numeric).
The dataset name has been kept as 'GPA_college_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, gpa_tbl_df, is a tibble containing survey data from 55 Duke University students. It includes information on students' GPA, weekly study hours, average hours of sleep per night, time spent going out per week, and gender. The dataset provides valuable insights into the relationship between academic performance and lifestyle habits.
data(gpa_tbl_df)
data(gpa_tbl_df)
A tibble with 55 observations and 5 variables:
Grade Point Average (numeric).
Number of hours spent studying per week (integer).
Average hours of sleep per night (numeric).
Average hours spent going out per week (numeric).
Gender of the student (factor with levels "Male" and "Female").
The dataset name has been kept as 'gpa_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, Grades_stats_tbl_df, is a tibble containing test grades for a beginning statistics class. It includes the grades of 29 students and provides insights into the performance distribution in an introductory statistics course.
data(Grades_stats_tbl_df)
data(Grades_stats_tbl_df)
A tibble with 29 observations and 1 variable:
Test grades (integer).
The dataset name has been kept as 'Grades_stats_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, gradestv_tbl_df, is a tibble containing simulated data for analyzing the relationship between the number of hours per week students watch TV and their grades in a statistics class. It provides a simple dataset for exploring correlations or regression models in educational settings.
data(gradestv_tbl_df)
data(gradestv_tbl_df)
A tibble with 25 observations and 2 variables:
Number of hours per week students watch TV (integer).
Grade obtained in a statistics class (integer).
The dataset name has been kept as 'gradestv_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, Graduate_tbl_df, is a tibble containing data on the graduation rates for student athletes in various schools within the Southeastern Conference. It includes the name of the school, a code for identification, and the graduation rate as a percentage.
data(Graduate_tbl_df)
data(Graduate_tbl_df)
A tibble with 12 observations and 3 variables:
Name of the school (character).
Code for the school (character).
Graduation rate as a percentage (integer).
The dataset name has been kept as 'Graduate_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Habits_tbl_df, is a tibble containing data on the study habits of students in two matched school districts. It includes variables related to the number of hours students from each district spent on studying, the difference between the two groups, and the significance of this difference.
data(Habits_tbl_df)
data(Habits_tbl_df)
A tibble with 11 observations and 4 variables:
Number of study hours in the first school district (integer).
Number of study hours in the second school district (integer).
Difference in study hours between the two school districts (integer).
Significance of the difference in study hours (numeric).
The dataset name has been kept as 'Habits_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, HedgesOlkin85_df, is a data frame containing data from Hedges and Olkin's 1985 study on the effects of open education. The dataset includes variables related to attitudes toward school and reading achievement in students, based on the meta-analysis reported in their work. This data was used to investigate the effects of open education.
data(HedgesOlkin85_df)
data(HedgesOlkin85_df)
A data frame with 4 observations and 6 variables:
Study identifier (numeric).
Effect size for attitude toward school (numeric).
Effect size for reading achievement (numeric).
Variance of the attitude effect size (numeric).
Covariance between attitude and achievement (numeric).
Variance of the achievement effect size (numeric).
The dataset name has been kept as 'HedgesOlkin85_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
The dataset was taken from the metaSEM package.
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.
This dataset, Homework_tbl_df, is a tibble containing data on the number of hours per week high school students spend on homework. The dataset compares students from private and public schools, providing insights into the study habits and academic workload of students in these two types of schools.
data(Homework_tbl_df)
data(Homework_tbl_df)
A tibble with 30 observations and 2 variables:
Type of school the student attends, either private or public (character).
Number of hours per week the student spends on homework (numeric).
The dataset name has been kept as 'Homework_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Jobsat_tbl_df, is a tibble containing data on job satisfaction and stress levels for 9 school teachers. The dataset provides insights into how teachers' stress levels relate to their job satisfaction, which can be valuable for understanding workplace dynamics and improving teacher well-being.
data(Jobsat_tbl_df)
data(Jobsat_tbl_df)
A tibble with 9 observations and 2 variables:
Stress level of the teacher, measured on a scale (integer).
Job satisfaction level of the teacher (numeric).
The dataset name has been kept as 'Jobsat_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Kinder_tbl_df, is a tibble containing data on the reading scores of first grade children who attended kindergarten versus those who did not. The dataset provides insights into the impact of attending kindergarten on early reading abilities, which can help in evaluating the effectiveness of early childhood education programs.
data(Kinder_tbl_df)
data(Kinder_tbl_df)
A tibble with 8 observations and 3 variables:
Pair identifier for the group of children (integer).
Reading score for children who attended kindergarten (integer).
Reading score for children who did not attend kindergarten (integer).
The dataset name has been kept as 'Kinder_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Lowabil_tbl_df, is a tibble containing data on the reading skills of 24 students with low abilities, who were matched based on certain characteristics. The dataset compares the performance of the students in two different groups: the experimental group and the control group. This can be used to evaluate the effectiveness of an intervention or treatment in improving reading skills.
data(Lowabil_tbl_df)
data(Lowabil_tbl_df)
A tibble with 12 observations and 3 variables:
Pair identifier for the matched students (integer).
Reading score for students in the experimental group (integer).
Reading score for students in the control group (integer).
The dataset name has been kept as 'Lowabil_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, major_survey_tbl_df, is a tibble containing information about the GPAs of 218 Duke students and their academic major. The dataset provides insights into the relationship between GPA and the field of study, allowing for an exploration of how academic performance varies across different majors.
data(major_survey_tbl_df)
data(major_survey_tbl_df)
A tibble with 218 observations and 2 variables:
Grade point average of the student (numeric).
Academic major of the student (factor with 3 levels).
The dataset name has been kept as 'major_survey_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, Math_scores_tbl_df, is a tibble containing the standardized math test scores of 30 students. The dataset is useful for analyzing the distribution of math scores and exploring factors that might influence math performance in educational settings.
data(Math_scores_tbl_df)
data(Math_scores_tbl_df)
A tibble with 30 observations and 1 variable:
Standardized math test score (integer).
The dataset name has been kept as 'Math_scores_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Mathcomp_tbl_df, is a tibble containing the standardized math competency scores for a group of 31 entering freshmen at a small community college. The dataset provides insights into the initial math skills of incoming students, which could be useful for evaluating preparedness and designing interventions to improve academic success.
data(Mathcomp_tbl_df)
data(Mathcomp_tbl_df)
A tibble with 31 observations and 1 variable:
Standardized math competency score (integer).
The dataset name has been kept as 'Mathcomp_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Mathpro_tbl_df, is a tibble containing information on math proficiency percentages, SAT math scores, and group classifications for 51 states in the United States. The dataset provides insights into how math proficiency and SAT scores vary by state, allowing for comparative analysis and exploration of regional trends in mathematics education.
data(Mathpro_tbl_df)
data(Mathpro_tbl_df)
A tibble with 51 observations and 4 variables:
Name of the state (character).
Average SAT math score for the state (integer).
Math proficiency percentage for the state (numeric).
Group classification for the state (integer).
The dataset name has been kept as 'Mathpro_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Miller_scores_tbl_df, is a tibble containing the Miller Personality Test scores for 25 college students applying for graduate school. This dataset allows for an exploration of personality traits and their potential correlation with academic or professional success.
data(Miller_scores_tbl_df)
data(Miller_scores_tbl_df)
A tibble with 25 observations and 1 variable:
Miller Personality Test score for a student (integer).
The dataset name has been kept as 'Miller_scores_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Music_tbl_df, is a tibble containing improvement scores for identical twins taught music recognition using two different techniques. Each pair of twins was taught using both methods, and the differences in their improvement scores were recorded.
data(Music_tbl_df)
data(Music_tbl_df)
A tibble with 12 observations and 3 variables:
Improvement scores using the first music recognition technique (integer).
Improvement scores using the second music recognition technique (integer).
Difference in improvement scores between the two methods (integer).
The dataset name has been kept as 'Music_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Parented_tbl_df, is a tibble containing information about the education levels of parents of 200 entering freshmen at a state university. The dataset provides insights into the distribution of parental education backgrounds and their possible influence on students' academic paths.
data(Parented_tbl_df)
data(Parented_tbl_df)
A tibble with 200 observations and 2 variables:
Education level of the parent (factor with 6 levels).
Parent type (factor with 2 levels: "mother" or "father").
The dataset name has been kept as 'Parented_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Prejudic_tbl_df, is a tibble containing scores measuring racial prejudice among a sample of 25 high school students. The dataset provides insights into attitudes related to racial prejudice within this demographic.
data(Prejudic_tbl_df)
data(Prejudic_tbl_df)
A tibble with 25 observations and 1 variable:
Racial prejudice score (integer).
The dataset name has been kept as 'Prejudic_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Program_stats_tbl_df, is a tibble containing information about the effects of four different methods of programmed learning on statistics students. It includes the learning method used and the corresponding scores of the students.
data(Program_stats_tbl_df)
data(Program_stats_tbl_df)
A tibble with 44 observations and 2 variables:
Programmed learning method (character).
Score obtained by the student (integer).
The dataset name has been kept as 'Program_stats_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, PSAT_SAT_tbl_df, is a tibble containing paired data on PSAT and SAT scores for a sample of students. It allows for the exploration of the relationship between performance on the PSAT and SAT exams.
data(PSAT_SAT_tbl_df)
data(PSAT_SAT_tbl_df)
A tibble with 7 observations and 2 variables:
PSAT scores (integer).
SAT scores (integer).
The dataset name has been kept as 'PSAT_SAT_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, QuizPulse10_df, is a data frame containing paired data on pulse rates for 10 students during a quiz and a lecture. The dataset allows for the exploration of how pulse rates differ during these two activities.
data(QuizPulse10_df)
data(QuizPulse10_df)
A data frame with 10 observations and 3 variables:
Student ID (integer).
Pulse rate during the quiz (integer).
Pulse rate during the lecture (integer).
The dataset name has been kept as 'QuizPulse10_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The original content has not been modified in any way.
The dataset was taken from the Lock5Data package.
This dataset, Readiq_tbl_df, is a tibble containing paired data on reading scores and IQ scores for a sample of individuals. It allows for the exploration of the relationship between reading ability and IQ scores.
data(Readiq_tbl_df)
data(Readiq_tbl_df)
A tibble with 14 observations and 2 variables:
Reading scores (integer).
IQ scores (integer).
The dataset name has been kept as 'Readiq_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, sat_improve_tbl_df, is a tibble containing simulated data on SAT score improvements for a sample of students who took a course from an SAT score improvement company. It allows for the exploration of score improvements from students who enrolled in the course.
data(sat_improve_tbl_df)
data(sat_improve_tbl_df)
A tibble with 30 observations and 1 variable:
SAT score improvement (integer).
The dataset name has been kept as 'sat_improve_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, Schizoph_tbl_df, is a tibble containing standardized exam scores for 13 patients. The data was collected to investigate the learning ability of schizophrenics after being given a specified dose of a tranquilizer.
data(Schizoph_tbl_df)
data(Schizoph_tbl_df)
A tibble with 13 observations and 1 variable:
Standardized exam scores (integer).
The dataset name has been kept as 'Schizoph_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, stats_scores_tbl_df, is a tibble containing the final exam scores of 20 students. The data provides insights into the academic performance of the students in their final exam for a statistics course.
data(stats_scores_tbl_df)
data(stats_scores_tbl_df)
A tibble with 20 observations and 1 variable:
Final exam scores (integer).
The dataset name has been kept as 'stats_scores_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, student_sleep_tbl_df, is a tibble containing the number of hours that 110 college students slept in a single night. The data allows for the analysis of sleep patterns among college students, potentially useful for understanding the relationship between sleep and academic performance, well-being, or other factors.
data(student_sleep_tbl_df)
data(student_sleep_tbl_df)
A tibble with 110 observations and 1 variable:
Number of hours slept (numeric).
The dataset name has been kept as 'student_sleep_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the openintro package.
This dataset, Study_freshmen_tbl_df, is a tibble containing the number of hours studied per week by a sample of 50 freshmen. It allows for the exploration of study habits and potentially provides insights into the relationship between study time and academic performance among college freshmen.
data(Study_freshmen_tbl_df)
data(Study_freshmen_tbl_df)
A tibble with 50 observations and 1 variable:
Number of hours studied per week (integer).
The dataset name has been kept as 'Study_freshmen_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, Tennessee_gifted_df, is a data frame containing the self-concept scores for 20 gifted high school students in Tennessee. It allows for the exploration of self-concept in the context of gifted students and may provide insights into their self-perception and potential academic achievement.
data(Tennessee_gifted_df)
data(Tennessee_gifted_df)
A data frame with 20 observations and 1 variable:
Self-concept scores for gifted students (numeric).
The dataset name has been kept as 'Tennessee_gifted_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The original content has not been modified in any way.
The dataset was taken from the BSDA package.
This dataset, TextbookCosts_df, is a data frame containing information about the number of textbooks and their total costs for different fields of study. It allows for the exploration of textbook expenses in various academic disciplines.
data(TextbookCosts_df)
data(TextbookCosts_df)
A data frame with 40 observations and 3 variables:
Field of study (factor with 4 levels).
Number of textbooks (integer).
Total cost of textbooks (integer).
The dataset name has been kept as 'TextbookCosts_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The original content has not been modified in any way.
The dataset was taken from the Lock5Data package.
This dataset, UCBAdmissions_table, is a contingency table containing aggregate data on applicants to graduate school at UC Berkeley in 1973. The data is classified by admission status, gender, and department, and it provides insights into admissions patterns for the six largest departments.
data(UCBAdmissions_table)
data(UCBAdmissions_table)
A contingency table with 24 cells (2 × 2 × 6), classified by:
Admission status (Admitted, Rejected).
Gender of the applicants (Male, Female).
Department (A, B, C, D, E, F).
The table entries are the number of applicants.
The dataset name has been kept as 'UCBAdmissions_table' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the educationR package and assists users in identifying its specific characteristics. The original content has not been modified in any way.
The dataset was taken from the datasets package.