11.2 The F-Distribution – Introduction to Statistics (2024)

LEARNING OBJECTIVES

  • Find the area under an [latex]F[/latex]-distribution.
  • Find the [latex]F[/latex]-score for a given area under the curve of an [latex]F[/latex]-distribution.

The [latex]F[/latex]-distribution is a continuous probability distribution. The graph of an [latex]F[/latex]-distribution is shown below. The [latex]F[/latex]-distribution is used in statistical inference to test the equality of population variances, test the difference in three or more population means, or to test the overall multiple regression model.

Properties of the [latex]F[/latex]-distribution:

  • The graph of an [latex]F[/latex]-distribution is positively-skewed and asymmetrical with a minimum value of 0 and no maximum value.
  • An [latex]F[/latex]-distribution is determined by two different degrees of freedom, [latex]df_1[/latex] and [latex]df_2[/latex]. [latex]df_1[/latex] is the degrees of freedom for the numerator of the [latex]F[/latex]-score and [latex]df_2[/latex] is the degrees of freedom for the denominator of the [latex]F[/latex]-score. The values of the degrees of freedom depends on how the [latex]F[/latex]-distribution is used. There is a different [latex]F[/latex]-distribution for every set of degrees of freedom. As the values of [latex]df_1[/latex] and [latex]df_2[/latex] get larger, the [latex]F[/latex]-distribution approaches a normal distribution.
  • The total area under the graph of an [latex]F[/latex]-distribution is 1.
  • Probabilities associated with an [latex]F[/latex]-distribution are given by the area under the curve of the [latex]F[/latex]-distribution.

USING EXCEL TO CALCULATE THE AREA UNDER AN [latex]\textcolor{white}F[/latex]-DISTRIBUTION

To find the area in the left tail:

  • To find the area under an [latex]F[/latex]-distribution to the left of a given [latex]F[/latex]-score, use the f.dist([latex]F[/latex], degrees of freedom 1, degrees of freedom 2, logic operator) function.
    • For [latex]F[/latex], enter the [latex]F[/latex]-score.
    • For degrees of freedom 1, enter the value of [latex]df_1[/latex] for the [latex]F[/latex]-distribution.
    • Fordegrees of freedom 2, enter the value of [latex]df_2[/latex] for the [latex]F[/latex]-distribution.
    • For logic operator, enter true.
  • The output from the f.dist function is the area to the left of the entered [latex]F[/latex]-score.
  • Visit the Microsoft page for more information about the f.distfunction.

To find the area in the right tail:

  • To find the area under an [latex]F[/latex]-distribution to the right of a given [latex]F[/latex]-score, use the f.dist.rt([latex]F[/latex], degrees of freedom 1, degrees of freedom 2) function.
    • For [latex]F[/latex], enter the [latex]F[/latex]-score.
    • For degrees of freedom 1, enter the value of [latex]df_1[/latex] for the [latex]F[/latex]-distribution.
    • Fordegrees of freedom 2, enter the value of [latex]df_2[/latex] for the [latex]F[/latex]-distribution.
  • The output from the f.dist.rt function is the area to the right of the entered [latex]F[/latex]-score.
  • Visit the Microsoft page for more information about the f.dist.rtfunction.

EXAMPLE

Consider an [latex]F[/latex]-distribution with [latex]df_1=12[/latex] and [latex]df_2=27[/latex].

  1. Find the area under the [latex]F[/latex]-distribution to the left of [latex]F=0.69[/latex].
  2. Find the area under the [latex]F[/latex]-distribution to the right of [latex]F=1.53[/latex].

Solution:

  1. Functionf.distAnswer
    Field 10.690.2535
    Field 212
    Field 327
    Field 4true
  2. Functionf.dist.rtAnswer
    Field 11.530.1738
    Field 212
    Field 327

USING EXCEL TO CALCULATE [latex]\textcolor{white}F[/latex]-SCORES

To find the [latex]F[/latex]-score for the a given left-tail area:

  • To find the [latex]F[/latex]-score for a given area under an [latex]F[/latex]-distribution to the left of the [latex]F[/latex]-score, use the f.inv(area to the left, degrees of freedom 1, degrees freedom 2) function.
    • For area to the left, enter the area to the left of required [latex]F[/latex]-score.
    • For degrees of freedom 1, enter the value of [latex]df_1[/latex] for the [latex]F[/latex]-distribution.
    • Fordegrees of freedom 2, enter the value of [latex]df_2[/latex] for the [latex]F[/latex]-distribution.
  • The output from the f.inv function is the value of [latex]F[/latex]-score so that the area to the left of the [latex]F[/latex]-score is the entered area.
  • Visit the Microsoft page for more information about the f.inv function.

To find the [latex]F[/latex]-score for the a given right-tail area:

  • To find the [latex]F[/latex]-score for a given area under an [latex]F[/latex]-distribution to the right of the [latex]F[/latex]-score, use the f.inv.rt(area to the right, degrees of freedom 1, degrees of freedom 2) function.
    • For area to the right, enter the area to the right of required [latex]F[/latex]-score.
    • For degrees of freedom 1, enter the value of [latex]df_1[/latex] for the [latex]F[/latex]-distribution.
    • Fordegrees of freedom 2, enter the value of [latex]df_2[/latex] for the [latex]F[/latex]-distribution.
  • The output from the f.inv.rt function is the value of [latex]F[/latex]-score so that the area to the right of the [latex]F[/latex]-score is the entered area.
  • Visit the Microsoft page for more information about the f.inv.rt function.

EXAMPLE

Consider an [latex]F[/latex]-distribution with [latex]df_1=37[/latex] and [latex]df_2=15[/latex].

  1. Find the [latex]F[/latex]-score so that the area under the [latex]F[/latex]-distribution to the left of [latex]F[/latex] is 0.413.
  2. Find the [latex]F[/latex]-score so that the area under the [latex]F[/latex]-distribution to the right of [latex]F[/latex] is 0.148.

Solution:

  1. Functionf.invAnswer
    Field 10.4130.934
    Field 237
    Field 315
  2. Functionf.dist.rtAnswer
    Field 10.2691.354
    Field 237
    Field 315

Concept Review

The [latex]F[/latex]-distribution is a useful tool for assessment in a series of problem categories. These problem categories include: statistical inference for two population variances, testing the equality of three or more population means (one-way ANOVA), and testing the overall significance of the multiple regression model.

Important parameters in an [latex]F[/latex]-distribution are the degrees of freedom in a given problem. The [latex]F[/latex]-distribution curve is skewed to the right, and its shape depends on the degrees of freedom. As the degrees of freedom increase, the curve of an [latex]F[/latex]-distribution approaches a normal distribution.

Attribution

13.3Facts About the F Distribution in Introductory Statistics by OpenStaxis licensed under aCreative Commons Attribution 4.0 International License.

11.2 The F-Distribution – Introduction to Statistics (2024)

FAQs

11.2 The F-Distribution – Introduction to Statistics? ›

The F -distribution is a continuous probability distribution. The graph of an F -distribution is shown below. The F -distribution is used in statistical inference to test the equality of population variances, test the difference in three or more population means, or to test the overall multiple regression model.

What is the F distribution in statistics? ›

It is a ratio of two independent chi-square distributions, each divided by their degrees of freedom. The F-Distribution has two parameters, the numerator degrees of freedom (df1) and the denominator degrees of freedom (df2).

What does F mean in statistics? ›

The F-test was developed by Ronald A. Fisher (hence F-test) and is a measure of the ratio of variances. The F-statistic is defined as: F = Explained variance Unexplained variance. A general rule of thumb that is often used in regression analysis is that if F > 2.5 then we can reject the null hypothesis.

How do you find the F distribution value? ›

In the F-sampling distribution, F is calculated by dividing the variance of one sample by the other sample's variance. For the right-tailed and two-tailed tests, keep the highest variance as the numerator and the lowest variance as the denominator.

How do you calculate the F-statistic? ›

Because we want to compare the "average" variability between the groups to the "average" variability within the groups, we take the ratio of the Between Mean Sum of Squares to the Error Mean Sum of Squares. That is, the F-statistic is calculated as F = MSB/MSE.

What does F test tell you? ›

F test is a statistical test that is used in hypothesis testing to check whether the variances of two populations or two samples are equal or not. In an f test, the data follows an f distribution. This test uses the f statistic to compare two variances by dividing them.

How do you find F in a probability distribution? ›

The formulas to find the probability distribution function are as follows:
  1. Discrete distributions: F(x) = ∑xi≤xp(xi) ∑ x i ≤ x p ( x i ) . Here p(x) is the probability mass function.
  2. Continuous distributions: F(x) = ∫x−∞f(u)du ∫ − ∞ x f ( u ) d u . Here f(u) is the probability density function.

What is a good F score in statistics? ›

Clearly, the higher the F1 score the better, with 0 being the worst possible and 1 being the best.

What does the F ratio tell us? ›

The F-ratio is defined as the ratio of the between group variance (MSB) to the within group variance (MSW). F = between group variance / within group variance = MSB / MSW. The calculated F-ratio can be compared to a table of critical F-ratios to determine if there are actually any differences between groups or not.

What is a high F-value? ›

The high F-value graph shows a case where the variability of group means is large relative to the within group variability. In order to reject the null hypothesis that the group means are equal, we need a high F-value.

Is F distribution positive? ›

The graph of the F distribution is always positive and skewed right, though the shape can be mounded or exponential depending on the combination of numerator and denominator degrees of freedom.

What is F in normal distribution? ›

Standard Normal Distribution

Let X be a continuous random variable. Then X takes on a standard normal distribution if its probability density function is f(x)=1√2πexp(−12x2). f ( x ) = 1 2 π e x p ( − 1 2 x 2 ) .

What is F distribution calculator? ›

F Distribution Calculator is a free online tool that displays the f value for the given f-distribution. BYJU'S online F distribution calculator tool makes the calculation faster and it displays the f value in a fraction of seconds.

What is a good significance F-value? ›

By rule of thumb, an F-value of greater than 4.0 is usually statistically significant but you must consult an F-table to be sure. If F is significant, than the regression equation helps us to understand the relationship between X and Y.

What does F-statistic mean in statistics? ›

An F-statistic is the ratio of two variances and it was named after Sir Ronald Fisher. Variances measure the dispersal of the data points around the mean. Higher variances occur when the individual data points tend to fall further from the mean.

What is the formula for the F distribution in statistics? ›

F = S 1 2 ∕ σ 1 2 S 2 2 ∕ σ 2 2 , where S 1 2 and S 2 2 represent the usual variance estimates of σ 1 2 and σ 2 2 , respectively, is a random variable having the F distribution.

What is F distribution vs t distribution? ›

The F distribution can be regarded as the equivalent extension of the t distribution when there is more than one variable but small sample sizes. There are numerous ways of introducing this distribution in the literature, which is widely employed in many diverse areas.

Why is F distribution always positive? ›

The F-distribution cannot take negative values, because it is a ratio of variances and variances are always non-negative numbers. The distribution represents the ratio between the variance between groups and the variance within groups.

What is the significance level of the F distribution? ›

If the F-test statistic is greater than or equal to 2.92, our results are statistically significant. The probability distribution plot below displays this graphically. The shaded area is the probability of F-values falling within the rejection region of the F-distribution when the null hypothesis is true.

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