Explain the meaning of r2 in this context. Choose the correct answer below.

Question

BlackTom AI · Accepted Answer

To understand r2 in this context, we first recall that r^2 (the coefficient of determination) measures how much of the variability in the dependent variable can be explained by the independent variable(s) in the model.

If the stated answer is that 'Age accounts for 89.2% of the variation in advertised price,' this is describing r^2 = 0.892. In plain terms, roughly 89.2% of the observed spread in advertised price can be attributed to differences in age as the predictor, assuming a simple linear relationship and the model assumptions hold.

It is important to note that r^2 does not tell us about causation. Even with a high r^2, we cannot conclude that age causes the price change; there could be confounding factors or correlations with other variables that drive the relationship.

Moreover, r^2 alone does not convey whether the model is appropriate. A high r^2 might occur due to overfitting if there are many predictors, or it could be inflated by outliers or nonlinearity that a simple linear model does not capture well.

In summary, interpreting r^2 as the proportion of variance in the price explained by age is correct, and 89.2% would imply a strong linear association between age and price in this dataset, while bearing in mind the usual caveats about causality, model suitability, and data quality.

BUSI_V 291 202 2024W2 Ch 04 Quiz Level 2

Explain the meaning of r2 in this context. Choose the correct answer below.

查看解析

登录即可查看完整答案

类似问题

Question at position 11 The coefficient of determination ………….. (Select all that apply)is used to evaluate the goodness of fitis equal to zero for a perfect fittakes values between –1 to +1is equal to negative one for the poorest fit

Calculate R^2 of the regression line for predicting height from shoulder girth, and interpret it in the context of the application.

The correlation coefficient for number of cans of beer and BAC is 0.89. Calculate R^2 and interpret it in context.

In a predictive regression model, in-sample R-squared is computed based on

R-Square question : What is R2 we define total sum of squares (TSS) the explained sum of squares (ESS) the residual sum of squares (RSS)

What is R2 with notations SSR = Sum of Squares REGRESSION SSE = Sum of Squares ERRORS SST = Sum of Squares TOTAL

The closer that the value of R2 is to 1, we would expect:

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