[1] 90 91 125 104 127 91
[1] 101.2454
[1] 31
[1] 312
This project analyzes Netflix movie duration using a dataset of Netflix titles.
[1] 90 91 125 104 127 91
[1] 101.2454
[1] 31
[1] 312
Call:
lm(formula = duration_num ~ release_year, data = movies)
Residuals:
Min 1Q Median 3Q Max
-107.557 -13.465 -1.783 13.595 213.535
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1234.41935 68.73329 17.96 <2e-16 ***
release_year -0.56291 0.03414 -16.49 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 25.62 on 5996 degrees of freedom
Multiple R-squared: 0.04337, Adjusted R-squared: 0.04321
F-statistic: 271.8 on 1 and 5996 DF, p-value: < 2.2e-16
The linear regression plot shows a slight negative relationship between release years and movies duration, indicating than more recent movies tend to be slightly shorter on average. However, the trend is weak, suggesting that movie durations have remained relatively stable over time. The variation in points also indicates the factors that factors other than release year likely influence movie length.
Overall, most movies are around 100 minutes long, with the majority falling between 90-120 minutes. While there is a slight decrease in duration over time, movie lenght has stayed fairly consistent overall.