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.
It determines the location of the graph: left or right - but not its shape.
It is 0.877
Right around -1.28
A variable that shows serious departure from the classic bell-shaped, or "Gaussian", curve is described as being not normally distributed. This departure could take the form of skew and/or kurtosis and/or multi modality.An example might be weekly wages. If you drew a histogram of a population's earnings you would most likely see a distribution skewed significantly toward the right. That is, toward the higher incomes.Another example is height. If you drew a histogram of a population's height you would see a bimodal distribution. One peak for males and another peak for females. The distribution of height for males and females might be normal when looked at individually, but not normal when you combine them.
It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.
The Z value is 0.
No, as you said it is right skewed.
the shape of the curve skewed is "right"
The graph shifts to the right.
Yes. Although all do not curve left or right, a curve in one direction or the other when hard is very common (i.e. normal)
The normal distribution is a bell shaped curve. Properly normalized, the area under the curve is 1.0. Start by drawing axes. The Y axis is probability, peaking at 0.4, crossing the X axis at the mean, and the X axis is standard deviation. Draw points (-3, 0.01), (-2, 0.05), (-1, 0.25), (0, 0.4), (+1, 0.25), (+2, 0.05), (+3, 0.01). These are all approximations. Connect the dots, understanding that the curve is asymptotic to the X axis.For a better picture, as well as an explanation, please see the related link below. This picture also shows you the percentage each area, grouped by standard deviation, or sigma, is. The normal distribution is the second picture on the right. Scroll up to see the picture, call "Normal Distribution".
From the table in the related link, the value at z equal one is 0.3413. The area then to the right of z equal one is 0.5 - 0.3413, or 0.1587.
In a business sense, it usually means a new employee is not quite keeping up with the 'learning curve' required to perform a particular job. In other instances it would mean 'off the pace' or 'behind schedule'. The origin of the phrase refers to the statistical bell shaped curve also called the normal probability distribution; where to be 'behind the curve' is to be analogously in area of the graph to the left of the bell curve, to be 'ahead of the curve' analogously in the area of the graph to the right of the bell curve.