README.md

In A-Farina/pl462: Data package and Templates for PL462

pl462

The goal of pl462 is to create a data package to simplify student and teacher workflows for PL462.

Installation

You can install the released version of pl462 from GitHub with:

library(remotes)
remotes::install_github("A-Farina/pl462")

Datasets:

stalker dataset

This dataset contains 78 observations and 3 variables (Therapy, AmtTher, Stalker).

Categorical Variables

• Therapy: Therapy Type (Cruel to be Kind Therapy, Psychodyshamic Therapy, None)
• AmtTher: Amount of Therapy (6 Weeks, 12 Weeks)

Continuous Variables

• Stalker: Time Spent Stalking (Hours per Week)

fugazi dataset

This dataset contains 90 observations and 3 variables (music, age, liking).

Categorical Variables

• music: Type of Music (Fugazi, Abba, Mantilow)
• age: Age of Listener (0-40 Years, 40+ Years)

Continuous Variables

• liking: Liking Rating

happyparent dataset

This dataset contains 302 observations and 7 variables (sex, health, educ, str_slf1, negmood1, children, str_chd).

Categorical Variables

• sex: Sex of Parent (male, female)
• educ: Education of Parent (Ranging from 8th Grade to PhD)

Continuous Variables

• health: Self-reported Physical Health
• str_slf1: Amount of Stress Related to Self
• negmood1: Negative Mood Rating of Parent
• children: Total Number of Children
• str_chd: Amount of Stress Related to Children

supermodel dataset

This dataset contains 231 observations and 4 variables (salary, age, years, beauty).

Continuous Variables

• salary: Salary per Day in British Pounds (0A3)
• age: Age in Years of Supermodel
• years: Number of Years as a Model
• beauty: Attractiveness (%)

cholesterol dataset

This dataset contains 18 observations and 5 variables (id, before, after4weeks, after8weeks, margarine). These data were contributed by Ellen Marshall, University of Sheffield as part of the Statstutor community project..

Categorical Variables

• margarine: Type of Margarine Consumed (A, B)

Continuous Variables

• id: Participant ID
• before: Cholesterol before the intervention (mmol/L)
• after4weeks: Cholesterol after four weeks (mmol/L)
• after8weeks: Cholesterol after eight weeks (mmol/L)

diet dataset

This dataset contains 78 observations and 8 variables (person, sex, age, height, preweight, diet_type, weight10weeks, weight_lost). These data were contributed by Ellen Marshall, University of Sheffield as part of the Statstutor community project..

Categorical Variables

• sex: Biological Sex of Participant (Male, Female)
• diet_type: Type of Diet Consumed (1, 2, 3)

Continuous Variables

• person: Participant ID
• age: Age of Participant (Years)
• height: Height of Participant (cm)
• preweight: Weight of Participant before intervention (kg)
• weight10weeks: Weight of Participant after 10 weeks (kg)
• weight_loss: Weight change of Participant (kg)

grit dataset

This dataset contains 432 observations and 5 variables (sex, athlete, id, class, grit).

Categorical Variables

• sex: Biological Sex (Female, Male)
• class: Timepoint of Measurement (Entry (Matriculation), Freshmen Spring, Yearling Spring)

Continuous Variables

• grit: Measure of Grit (Scale Score based on a 5-point Likert Scale)

A-Farina/pl462 documentation built on May 9, 2022, 1:52 p.m.