Questions tagged [f-statistic]

An F statistic is a value you get when you run an ANOVA test or a regression analysis to find out if the means between two populations are significantly different.

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How can the F statistic of my anova test be greater than 1?

I've been digging into the formula for one way ANOVA test and I understand the we obtain the results from the ANOVA analysis with: ...
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Why Does Sample Size Affect the Value of F-Statistic We Require to Reject the Null Hypothesis of No Relationship?

In studying for multiple linear regression, I came across a comment that says that given a large sample, a F-statistic slightly larger than 1 could suggest there is some relationship between the ...
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When to include or reject interaction term in two variable linear regression

I am studying a treatment that degrades device quality and performed an independent sample test on two batches that had different initial quality. I analyzed the data with a two variable linear ...
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Why does the J-test yield a $\chi^2$ distribution?

My econometrics professor recently introduced us to the J-test. To perform the J-test, he gave us the following procedure: Estimate $\mathbf{b}^{2SLS}$ and using this, define $\hat{U}_n$ residuals ...
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F-test differences Stata and R

I have a question about what the difference is in how Stata and R compute ANOVAs. I have run exactly the same ANOVA in both softwares, but curiously get a different F-statistics for one of the ...
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The square of each t-statistics is the corresponding F-statistics

The below text is from statistical learning Page 76-77. The data used in the following example can be found here . I just want to know how to calculate $RSS_0$ (It is different from TSS) As ...
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What's the value of f1 score when true positives are zero? [duplicate]

f1 score is defined as F1 = 2 * (precision * recall) / (precision + recall) However if true positives are zero, this gives 0/0. How to deal with this scenario?
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Justification for AIC/BIC vs F-statistic when using stepwise backward elimination

I note that some stepwise backwards elimination methods use AIC to make the decision about which variables to eliminate, and others use the F-statistic. Why would I use one over the other, and is ...
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R-squared and F-stat in dummy variables regression vs panel FE model

When estimating a Fixed Effects model on panel data and an equivalent dummy variables regression, the coefficient estimates and associated SEs are identical. However, the R-squared and F-statistic are ...
392 views

Why ever use F-statistic?

We can use F-statistic for determining whether at least one of the predictors has an effect on the response. But why just not take minimal p-value across all predictors? It doesn't require introducing ...
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Out Of Time variance test method and threshold for logistic regression models

I am interested in designing a test statistic for checking the out-of-time variance of a logistic regression model relative to the model development sample at an observation level. We did something ...
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Interpreting the f ratio in linear regression in r

The last string of my output in r is: F-statistic: 181.4 on 15 and 2380 DF, p-value: < 2.2e-16 How do I interpret this result? While I understand that the f value is a ratio that compares the ...
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Why OLS F Statistic close to one when there is no relationship?

I might be missing something obvious here. In linear regression, F statistic is defined as (explained variance / p) / mean squared error, where p is number of independent variables. When there is no ...
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Assessing strength of instrument

I want to use a risk score (RS) as an instrument for an exposure on a clinical outcome. However, I wont have access to data on the outcome for some time, and wish to examine whether this risk score ...
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How to compute F-statistics for each features of regression models in glmnet? [duplicate]

I have learned lot's of Lasso regression models(20000) using glmnet. I need to compute somehow test statistics for each features of models. like F-statistics,... Can I do this using bootstrapping ? ...
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What is the benefit of knowing the F statistic in multiple linear regression?

One of the basic figures you get when running multiple linear regression using almost any off-the-shelf software is the F statistics. However, I cannot recall one situation, where the F value was low ...
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F stats for post hoc test of a linear mixed effects model

I have an unbalanced linear mixed effects model with three fixed factors of various levels and one random factor for my repeated measures data (for details see here). Thanks to your help I managed to ...
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Is it possible to get a negative F-statistic (e.g. in ANOVA)?

If so, why? If not, why not? I'm thinking of an ANOVA context, but if the answer changes depending on context I would also be interested to know why that is.