Introduction

This report analyzes a dataset containing information about students’ study habits, AI usage, grades, and daily screen time. The purpose of this analysis is to summarize the dataset using descriptive statistics and visualizations, and to interpret patterns related to academic behavior and the use of artificial intelligence tools.

Descriptive Statistics

The table below provides basic descriptive statistics for the dataset, including summary measures (minimum, first quartile, median, mean, third quartile, and maximum) for numeric variables and counts for categorical variables.

##       age        education_level    study_hours_per_day   uses_ai         
##  Min.   :14.00   Length:100         Min.   :1.000       Length:100        
##  1st Qu.:15.00   Class :character   1st Qu.:1.975       Class :character  
##  Median :16.00   Mode  :character   Median :2.800       Mode  :character  
##  Mean   :16.49                      Mean   :2.987                         
##  3rd Qu.:18.00                      3rd Qu.:4.025                         
##  Max.   :19.00                      Max.   :5.000                         
##  ai_tools_used      purpose_of_ai      grades_before_ai grades_after_ai
##  Length:100         Length:100         Min.   :55.00    Min.   :55.0   
##  Class :character   Class :character   1st Qu.:59.00    1st Qu.:61.0   
##  Mode  :character   Mode  :character   Median :63.00    Median :69.0   
##                                        Mean   :64.77    Mean   :68.7   
##                                        3rd Qu.:70.00    3rd Qu.:74.0   
##                                        Max.   :75.00    Max.   :89.0   
##  daily_screen_time_hours
##  Min.   :2.00           
##  1st Qu.:3.00           
##  Median :4.00           
##  Mean   :4.34           
##  3rd Qu.:6.00           
##  Max.   :7.00

Graph:1

This histogram shows how study hours per day are distributed across students. Taller bars represent study-hour ranges that occur more frequently. This plot helps identify the typical amount of studying and whether there are students who study unusually little or unusually much. If the bars extend farther on one side, the distribution may be skewed.

Graph:2

This bar chart shows the number of students in each education level category. Larger bars indicate that more students fall into that category. This is useful context because education level may relate to study habits, screen time, and AI usage.

Graph:3

This graph compares how many students report using AI versus not using AI. A noticeable difference in bar heights indicates whether AI usage is common in this dataset.

Graph:4

This boxplot compares grade distributions before and after AI use. The median line shows the typical grade value, while the box displays the middle 50% of grades. A higher median after AI use suggests possible grade improvement.

Graph:5

This scatter plot explores whether daily screen time is associated with changes in grades. Each point represents a student. Positive values indicate grade improvement, while negative values indicate grade decline. The trend line summarizes the overall relationship.

Conclusion:

This report presented descriptive statistics and five visualizations to summarize student study behavior and AI usage. The results highlight patterns in study hours, education level, AI adoption, grade changes, and screen time. These findings provide a foundation for further statistical analysis to evaluate whether the observed patterns are statistically significant.