What determines whether a coefficient estimate is statistically significant?

Question

BlackTom AI · Accepted Answer

Question: What determines whether a coefficient estimate is statistically significant?

Option 1: 'Adjusted R Square.' Adjusted R-squared measures the proportion of variance explained by the model, adjusted for the number of predictors. It reflects model fit, not the individual significance of a single coefficient, so it does not determine whether a particular coefficient estimate is statistically significant.

Option 2: 'The magnitude of the coefficient.' The size of the coefficient tells you the practical or economic impact of a unit change in the predictor, but statistical significance depends on uncertainty around the estimate (standard error) and the corresponding p-value. A large magnitude can still be not statistically significant if the estimate is imprecise.

Option 3: 'R Square.' R-squared is a general measure of how much of the outcome variance is explained by the model. Like adjusted R-squared, it pertains to overall model fit rather than the significance of an individual coefficient, so it does not determine significance of a single parameter.

Option 4: 'P-value of the t-stat.' This is the correct concept: the statistical significance of a specific coefficient is assessed by the t-statistic, which is the ratio of the coefficient estimate to its standard error. The p-value from this t-test indicates whether we can reject the null hypothesis that the coefficient equals zero at a given significance level.

Option 5: 'P-value of the F-test.' The F-test p-value assesses whether the model (as a whole) provides a better fit than a model with no predictors, i.e., overall significance, not the significance of an individual coefficient. While related to model validity, it does not determine the significance of a single coefficient.

What determines whether a coefficient estimate is statistically significant?

查看解析

登录即可查看完整答案

类似问题

Which variables were significant in your model? (Use an alpha of 10% to draw your conclusions.)

A researcher conducts a study and finds a statistically significant difference between two groups. Which of the following statements is NOT necessarily true?

Based on the information provided in Q1, which of the following is true?

With large sample sizes, even small differences between the null value and the observed point estimate, a difference often called the effect size, will be identified as statistically significant.

What does it mean for results to be statistically significant?

Reinhart points out that if a researcher runs an experiment and collects a huge sample of data then there is a high chance that they will find a statistically significant value for p when they do the analysis. This implies that:

Martin has found a correlation of r =.18 between the two variables of using prescription stimulants (e.g., Adderall) and frontal lobe activity. This correlation is more likely to be statistically significant if

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