Adjusted R squared is use to account for which?

Question

BlackTom AI · Accepted Answer

When evaluating regression models, various metrics are used to understand fit and avoid overfitting. 
Option 1: 'y intercept' – The intercept is a parameter of the model, not something that adjusted R-squared specifically accounts for. Adjusted R-squared does not adjust for the intercept term directly, so this is not the correct focus. 
Option 2: 'variance covariance matrix' – While the variance-covariance matrix describes parameter uncertainty, adjusted R-squared is not defined in terms of this matrix; it is a different diagnostic that penalizes additional predictors. Therefore this choice misstates the purpose. 
Option 3: 'the number of independent variables' – This is the crux of adjusted R-squared: it increases with predictors only if they improve the model more than would be expected by chance, and it penalizes each additional variable to counter overfitting. This aligns with the idea of adjusting for model complexity. 
Option 4: 'the number of observations' – Although the sample size affects standard errors and test statistics, adjusted R-squared itself is not a direct adjustment for the number of observations; it adjusts for the number of predictors relative to sample size, not merely the count of observations. Hence this option is not the primary purpose. 
In summary, the concept behind adjusted R-squared is to account for model complexity by incorporating the number of independent variables into the metric, preventing the artificial inflation of fit when adding predictors that do not meaningfully improve the model.

ERMCPS5350_003_2025_3 - INTRO TO QUANTITATIVE RISK MANAGEMENT 13. Quiz for Class 13

Adjusted R squared is use to account for which?

查看解析

登录即可查看完整答案

类似问题

What is the relationship between Adjusted R-Square and R-Square?

What is the relationship between Adjusted R-Square and R-Square?

At times, adjusted R^2 is used instead of R^2 in order

Suppose we regress student’s ATAR scores on parent’s education and parent’s income. If we run the regression again but also include the student’s height as an additional regressor:[Fill in the blank]

Why is the adjusted R2 more informative than the R2?

Why may we opt for the adjusted r2 instead of the multiple r2 when assessing model fit of multiple linear regression?

更多留学生实用工具

考试浏览器助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单