Stack Exchange Network

Stack Exchange network consists of 175 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange

Questions tagged [f-test]

Any hypothesis test in which the statistic has an F distribution under the null hypothesis.

3
votes
1answer
43 views

groups, levels and denominator dof in mixed effect models

I am trying very hard (I am not a statistician) to understand the concepts of "groups" and "levels" in mixed effect models. In particular, I am trying to understand this in the context of the ...
0
votes
1answer
39 views

Finding value of f statistic to test for difference between treatment means given the following table

Im not really good with statistics and cant really find a way to answer this question. Finding value of f statistic to test for difference between treatment means given the following table.
0
votes
0answers
27 views

In the F test, is a two-sided test mainly used?

I have a question about the F test. In R language, three parameters "two.side", "less" and "greater" can be specified as arguments of var.test (). However, I can not specify a one-sided test like "...
1
vote
1answer
17 views

$F$-test with a variance being $C$ times as large as the other

I am familiar with $F$-tests in which the alternative hypothesis is defined as $H_a=\{\sigma^2_1/\sigma^2_2>C\}$ (the sign "$>$" can be either "$<$" or "$\ne$" as well), where $C=1$. If I ...
2
votes
1answer
21 views

How to interpret $F > F_{\rm crit}$, but $p > \alpha$

My F is greater than F critical, while P-Value is 0.99 greater than alpha (0.05) which one should I consider the P value or F statistic, rejecting the Ho: I am confused. Edit: $$ \begin{array}{ccc} \...
0
votes
0answers
9 views

F test, Model selection test

How to compare which of the following two models is a better fit: M1 $y$ = $\alpha$$X$ + $\epsilon$ M2 $ln(y)$ = $\alpha$$X$ + $\epsilon$ Can we run a test statistic to compare the two models? ...
5
votes
1answer
3k views

Comparing two F-test statistics

I have two groups A and B, each of which consists of 5 samples. Each sample is described in a vector of length (>1000) of continuous numeric values (characteristics). I want to test if the sample in ...
1
vote
2answers
41 views

I have an insignificant beta weight of a predictor, which the only predictor in a step with significant R-square change and significant F-value

I am running a hierarchichal multiple linear regression with 4 steps containing theoretically justifyable variables: Outcome: pain rating Step 1: demographic variables (age, gender) Step 2: Pain ...
0
votes
1answer
26 views

Two sample T test frequency table

I am struggling with a data analysis. I have made a survey and got the following answers in the first turn, I put them in a frequency table Don't agree at all: 8 Don't agree: 6 I don't know: 16 ...
0
votes
0answers
19 views

Permutation F test for nested models

How can I do a permutation F test for testing if a larger model which contains a larger model is better? e.g. Model 1 : y ~ x1 + x2 Model 2 : ...
6
votes
3answers
28k views

Prove F test is equal to T test squared

I need to show that F test is equal to T test squared, when the T test is for 2 independent groups and assuming variances are equal. I know that $F=\frac{MSB}{MSW}=\frac{SSB/k-1}{SSW/N-K}$ and I know ...
4
votes
1answer
5k views

Is F test used for feature selection only for features with numerical and continuous domain?

The F-statistic/test can be used for feature selection, e.g. from http://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html#sklearn.feature_selection.f_classif ANOVA ...
0
votes
1answer
49 views

OLS: why is it possible to get insignificant F-test but resonably high adjusted R-squared?

I am estimating an OLS regression with 158 observations and about 140 regressors (some unstructured data features to personality measure). Below is the bottom output I get from OLS. Some of the ...
0
votes
1answer
30 views

Interpreting ANOVA f-test for model comparison

In the book ISLR, there's a lab activity which compares the nested models. ...
2
votes
1answer
45 views

What is the point of a permutation F-test when all you need is one F-test for one-way ANOVA?

Say you have three groups, and each group has 5 observations. You can figure out if there is a significant difference between means with a simple one-way ANOVA. I read in my nonparametric book, one ...
0
votes
1answer
40 views

What is the difference between the residual, lack of fit and pure error In F test for Regression Analysis?

What is the difference between the residual, lack of fit and pure error and how to calculate each of them in ANOVA F test for nonlinear regression?
1
vote
1answer
256 views

Why does anova F-test give different results for a categorical variable added as factor and as continuous?

I'm comparing the addition of a variable in my linear model using R and "anova F-test": anova(fit1,fit2) What I noticed is that this F-test produces different ...
1
vote
1answer
239 views

Significant omnibus f-test but planned comparison testing showing no evidence of effect

i'm testing the relationship between four age groups of teachers on their perceived level of job security. I've run an omnibus f-test on some data, 240 subjects- no examples of any skewness, and it ...
1
vote
1answer
821 views

Using F-test for (generalised) linear models

I am working with regression on a data set and I am looking for a way to compare the results. From the data ($x$) and observed values ($y$) where $y\in[0, 1]$, I have three models: 1 (baseline): ...
1
vote
1answer
48 views

Is it possible to calculate F-value for a neural network regression model?

I trained a model using neural network regression and used the F-value equation that is used for calculating F-value for linear regression: F=(SUM(Ypredicted-Ymean)^2/p)/(SUM(Ypredicted-Yobserved)^2/...
1
vote
0answers
38 views

F-test in multiple linear regression

I'm currently reading Introduction to statistical learning. When trying to prove the collective significance of a regression linear model, we use the F-test with the following formula. $$F=\frac{(TSS-...
2
votes
1answer
24 views

Test for ratio of variances across multiple groups

I am looking for a statistical test for whether the ratio of variances vary significantly among groups. I have 100 groups, each with ~50 A individuals and ~50 B individuals (n varies somewhat between ...
3
votes
2answers
7k views

Is a partial F-Test on a model reduced by only one variable valid?

For a recent project, I used multiple linear regression to model data. I attempted to choose between my initial full model and a reduced model by performing a partial F-test. The models used were the ...
16
votes
2answers
4k views

Why is F-test so sensitive for the assumption of normality?

Why is the F-test for difference in variance so sensitive to the assumption of normal distribution, even for large $N$? I have tried to search the web and visited the library, but none of it gave any ...
1
vote
1answer
59 views

Alternative to Chow test in the case of heavy tailed residual distribution

I would like to check if two subpopulations of my data have the same parameters in a model. Model 1 is based on subpopulation 1 and Model 2 is based on subpopulation 2. Model 1: $y=x^\alpha + \...
3
votes
0answers
17 views

F test fails but t-test does not? [duplicate]

I'm a bit confused about this. I have a model with multiple variables trying to explain the dependent variable. When I use the F test, I don't pass the critical value. But when I seperate the ...
2
votes
1answer
2k views

If the f-test is insignificant but coefficients are significant, can I use it?

If the linear regression's f-test is insignificant but its coefficients are significant in t-test, can I use this regression and its coefficients? In academic journals, I find people use linear ...
3
votes
1answer
10k views

F test and t test in linear regression model

F test and t test are performed in regression models. In linear model output in R, we get fitted values and expected values of response variable. Suppose I have height as explanatory variable and ...
1
vote
1answer
72 views

Testing nested models with clustered errors

I have a simple linear model. $$Y_i = \beta_1X _{1i}+ \beta_2X_{2i}+\beta_3X_{3i}+\epsilon_i$$ I'd like to test if some of my model parameters ($\beta_2$ and $\beta_3$) are jointly different from ...
0
votes
0answers
34 views

How should one compute the p-values of a two sided F test?

I have been studying this link. However, i can't really figure out how to calculate the p value for a 2 sided F test where the degrees of freedom are different and the F distribution is asymmetric. I ...
0
votes
0answers
88 views

What is the point in reporting the z statistic of a z-test?

In my field some authors report the z statistic of a z-test in a generalised linear model and others do not. Does reporting the z statistic serve any purpose if the p value of a z-test or of a post-...
6
votes
1answer
119 views

Comparison of variance between two samples with unequal sample size

The primary goal of my analysis is to compare the variability in the response variable, Blood Pressure, between sample1 and sample2. The secondary goal is to test for a difference in means. I do not ...
0
votes
0answers
10 views

Can I mix and match F-test and T-test code when I implement a program for some statistical calculations?

I was told to rewrite an old java program that performs some statistical calculations. I was able to solve most of the problems until I ran into this one: The program compares two sets of data over ...
1
vote
0answers
39 views

Test the difference between average value of 2 random variables

I am doing an exercise on marketing analysis to determine the strategy that a brand should follow based on historical weekly data collected from supermarkets that sell the brand (let say brand1) and 4 ...
1
vote
0answers
22 views

Why is it possible to get insignificant F statistic (p>0.1) but significant regressor t-tests (p<0.1)? [duplicate]

My results show significant t-tests but an insignificant F-test. Is this possible or are my calculations wrong?
1
vote
0answers
70 views

Is this an appropriate way to compare simulated and measured data with small sample size, and are there alternatives?

I have a probably fairly basic question which I couldn't find an answer to on here or anywhere else. Would really appreciate any thoughts on this :) I am modelling the propagation of sound through a ...
0
votes
0answers
16 views

Can an F-Test be worse than the two single T-Tests? [duplicate]

Normally when conducting an F-Test one is hoping the F-Test of all variables is significant although the single T-Tests yield insignificant results. But can the reverse also be true? That is a worse ...
12
votes
1answer
1k views

Sample size formula for an F-test?

I am wondering if there is a sample size formula like Lehr's formula that applies to an F-test? Lehr's formula for t-tests is $n = 16 / \Delta^2$, where $\Delta$ is the effect size (e.g. $\Delta = (\...
0
votes
0answers
46 views

I can perform an F-Test if Bartlett and Levene fail, but Shapiro-Wilk Pass?

I'm going through the assumptions on an F-test and I want to make sure I've gone through each item so that my results are valid. Data is normally distributed; The samples are independent from one ...
0
votes
0answers
144 views

Are these Granger-causality F-tests equivalent?

I am comparing results of a Granger causality implementation I wrote in Python to the established package statsmodels, and noticed that the equation implemented has a scaling factor equal to the ...
1
vote
0answers
43 views

Is the F-test (especially in stepwise regression context) problematic for huge datasets?

Let's say I have a huge dataset with 2000 observations. I want to test the significance of one predictor in a SLR Model. Then the F-statistic effectively becomes: F = $\frac{\frac{\sum{(\hat{Y_i}-\...
2
votes
0answers
132 views

R - Testing for Granger causality when OLS assumption are violated

I am using the vars package to estimate a VAR-model. Since it seems, that the residuals of my model are neither homoscedastic or uncorrelated I computed Newey West ...
0
votes
0answers
50 views

Why do dummy regressors decrease sensitivity in linear regression?

For linear regression analysis, I thought that the addition of covariates which are not related to the dependent variable $Y$ does not decrease sensitivity. Such random/dummy regressors can be ...
2
votes
1answer
36 views

Which test do you suggest to use to catch the differences in paired sample

I must evaluate the goodness of an instrument according to the measures of the final products. I have two instruments: one good and the other one whose goodness I have to evaluate. The measures are ...
1
vote
0answers
47 views

Stable seasonality F-test does not meet assumptions for one way ANOVA

I am having trouble to understand Stable seasonality F-test. I know it is basically the same test as one way ANOVA, but the assumptions for one way ANOVA can´t be met for it. For ANOVA the data should ...
3
votes
0answers
25 views

Can I use F test to compare linear and exponential model?

I have a data set consisting of crop biomass measurements ("response" variable) and corresponding spectral vegetation indices measurements (predictor variables). The measurements have been made on two ...
4
votes
1answer
347 views

Is an F-test for equality of variance appropriate for a very large dataset?

I have a dataset with about 500,000 subjects and I am trying to establish whether the variance is equal. I first performed an F-test but then I realised the data is slightly skewed with kurtosis. So ...
0
votes
0answers
25 views

Deriving the F-test from ${{SSE_R-SSE_F}\over{(n-q)-(n-p)}}/{{SSE_F}\over{n-p}}$

Given a Full and Reduced model, the F-test to see if the reduced model is significant is given by $$ {{SSE_R-SSE_F}\over{(n-q)-(n-p)}}/{{SSE_F}\over{n-p}} $$ I'm trying to understand how this is ...
2
votes
2answers
308 views

Why does it says data should be normally distributed for analysis, when different test follow its own distribution (i.e. t, Z, F)?

Why does it say data should be normally distributed for statistical analysis when different test follow its own distribution (i.e. t, Z, F)? What does normality have to do with this?
1
vote
0answers
182 views

How does the f-classif in scikit-learn work?

Does it combine different features and calculate the F-value between them or does it does calculate the F-value for one feature? If someone could point me to a source a book that explain this, that ...