student: Multifaceted Computer Science Students Data To Identify...

In rcollectadhd: Collection of Data Sets Containing ADHD Related Data

Multifaceted Computer Science Students Data To Identify Depression Level

Description

This dataset comprises survey results from 100 computer science students, aiming to identify correlations between their depression levels, class performance, and ADHD patterns through data analysis. This dataset is designed to facilitate a comprehensive analysis of the interplay between demographic factors, academic performance, mental health, study habits, and social dynamics among individuals in the specified context.

Usage

student

Format

a data frame with 10 columns:

Age

(factor) Age of each individual.

Gender

(factor) Gender of individual.

AcademicPerformance

(factor) Academic performance of each individual.

TakingNoteInClass

(factor) Note taking habits of each individual.

DepressionStatus

(factor) Presence of depression symptoms reported by each individual.

FaceChallengesToCompleteAcademicTask

(factor) Experience of facing challenges in completing academic challenges reported each individual.

LikePresentation

(factor) Like for making presentations for each individual.

SleepPerDayHours

(numeric) Average hours of sleep obtained reported by each individual.

NumberOfFriend

(numeric) Number of friends each individual reported having.

LikeNewThings

(factor) Like for new things reported by each individual.

Source

"Psychosocial Dimensions of Student Life" authored by Md. Ismiel Hossen Abir on Kaggle: https://www.kaggle.com/datasets/mdismielhossenabir/psychosocial-dimensions-of -student-life Last retrieved from Kaggle: 2024-10-12

rcollectadhd documentation built on Nov. 1, 2024, 5:07 p.m.