When comparing the sums of squares of normal variates.
No.It is asymmetric.
The exponential distribution is a continuous probability distribution with probability density definded by: f(x) = ke-kx for x ≥ 0 and f(x) = 0 otherwise.
Given U_i~χ_(ν_i)^2, (U_1/ν_1)/(U_2/ν_2 ) follows which distribution? F_(ν_1,ν_2 ) F Probability Distribution with ν degree of freedom Given T=Z/√(U/ν), Z~N(0,1) and U~χ_ν^2, T^2 follows an F-Distribution F_(1,ν) F Probability Distribution with one degree of freedom in the numerator and ν in the denominator
The parent probability distribution from which the statistic was calculated is referred to as f(x) and cumulative distribution function as F(x). The sampling distribution and cumulative distribution of a statistic is commonly referred to as g(y) and G(y) where Y is the random variable representing the statistic. There are numerous other notations.
When comparing the sums of squares of normal variates.
The F distribution can't be negative.
The F-distribution is either zero or positive, so there are no negative values for F. This feature of the F-distribution is similar to the chi-square distribution. The F-distribution is skewed to the right. Thus this probability distribution is nonsymmetrical.
In general the distribution of F-ratio means what
No, it is continuous.
Yes.
The F distribution is used to test whether two population variances are the same. The sampled populations must follow the normal distribution. Therefore, as the sample size increases, the F distribution approaches the normal distribution.
No they are not the same.
No.It is asymmetric.
Characteristics of the F-distribution1. It is not symmetric. The F-distribution is skewed right. That is, it is positively skewed.2. The shape of the F-distribution depends upon the degrees of freedom in the numerator and denominator. This is similar to the distribution and Student's t-distribution, whose shape depends upon their degrees of freedom.3. The total area under the curve is 1.4. The values of F are always greater than or equal to zero. That is F distribution can not be negative.5. It is asymptotic. As the value of X increases, the F curve approaches the X axis but never touches it. This is similar to the behavior of normal probability distribution.
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The exponential distribution is a continuous probability distribution with probability density definded by: f(x) = ke-kx for x ≥ 0 and f(x) = 0 otherwise.