Analysis of Music-Listening Habits and Mood Changes During Daily Activities Using Multiple Linear Regression

Abstract

Music is commonly used during daily activities for entertainment, concentration, and mood regulation. However, the relationship between music-listening habits and perceived mood changes may vary across individuals and listening contexts. This study aims to explore music-listening patterns and examine the association between selected listening habits and perceived mood changes using Exploratory Data  Analysis (EDA) and multiple linear regression. The study used survey data from 150 respondents. Data preprocessing included removing personal identification columns, checking missing values and duplicate records, inspecting potential outliers using the Interquartile Range (IQR) method, and encoding categorical variables using one-hot encoding. EDA was conducted using descriptive statistics, distribution plots, scatter plots, and Pearson correlation analysis. The initial regression model included 11 predictors and produced an R² of 0.235 and an adjusted R² of 0.174, with an overall F-statistic of 3.863 and a p-value of 7.19 × 10⁻⁵. Diagnostic testing indicated non-normal residuals and heteroskedasticity. Therefore, the final model used heteroskedasticity-consistent HC3 standard errors and included two predictors: the percentage of daily activities perceived as more comfortable with music and the indicator for listening without a specific time. The final model achieved an R² of 0.1503 and an adjusted R² of 0.1387. Both predictors were statistically significant in the final model. These findings suggest that perceived comfort when listening to music and listening-time patterns are associated with reported mood changes. Nevertheless, the observational survey design and limited explanatory power mean that the results should not be interpreted as evidence of causation.

Keywords: exploratory data analysis, music-listening habits, mood changes, multiple linear regression, HC3 robust standard errors