Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.
A skewed distribution typically has one tail that is longer or fatter than the other. In a right-skewed distribution, the tail on the right side is longer, while in a left-skewed distribution, the left tail is longer. Therefore, a skewed distribution has one dominant tail, but it can be characterized by its direction (right or left).
Higher skewness indicates a greater asymmetry in the distribution of data points around the mean. A positive skew means that the tail on the right side of the distribution is longer or fatter, while a negative skew indicates the opposite, with a longer or fatter left tail. In practical terms, higher skewness can suggest potential outliers and may affect statistical analyses that assume a normal distribution.
Skewness is a statistical measure that indicates the degree of asymmetry of a distribution around its mean. A positive skewness means that the tail on the right side of the distribution is longer or fatter, while negative skewness indicates a longer or fatter tail on the left side. In essence, skewness helps to understand the direction and extent to which a dataset deviates from a normal distribution. It is often used in data analysis to assess the distribution characteristics and make informed decisions based on the data.
A normal distribution is not skewed. Skewness is a measure of how the distribution has been pulled away from the normal.A feature of a distribution is the extent to which it is symmetric.A perfectly normal curve is symmetric - both sides of the distribution would exactly correspond if the figure was folded across its median point.It is said to be skewed if the distribution is lop-sided.The word, skew, comes from derivations associated with avoiding, running away, turning away from the norm.So skewed to the right, or positively skewed, can be thought of as grabbing the positive end of the bell curve and dragging it to the right, or positive, direction to give it a long tail in the positive direction, with most of the data still concentrated on the left.Then skewed to the left, or negatively skewed, can be thought of as grabbing the negative end of the bell curve and dragging it to the left, or negative, direction to give it a long tail in the negative direction, with most of the data still bunched together on the right.Warning: A number of textbooks are not correct in their use of the term 'skew' in relation to skewed distributions, especially when describing 'skewed to the right' or 'skewed to the left'.
It is 0.158655, approx.
0.0668 or about 1/15
It is 0.158655 or 0.159 approx.is the anwer 0.8413, -0.3413, -0.1587, 0.1587
11.51% of the distribution.
2.27%
2.27
Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.
it is the test one tail
The domain of the Normal distribution is the whole of the real line. As a result the horizontal axis is asymptotic to the Normal distribution curve. The curve gets closer and closer to the axis but never, ever reaches it.
It is .121
Z = -0.8416
A normal distribution has a mean of = 60 and a standard deviation of = 20. for each of the following scores, indicate weather the tail of the distribution is to the left or the right of the score, and find the proportion of the distribution of the tail.a. x= 75b. x=65c. x= 50d. x= 30 ____________________________________________________________________________ find each of the following probabilities for a normal distribution:a. p(z>-1.00)b. p(z>-0.80)c. p(z<0.25)d. p(z<1.25) ____________________________________________________________________________ for a normal distribution idenitfy the z-score location that would separate the distriubtion into two sections so there is:a. 70% in the body on the right-hand side.b. 80% in the body on the right-hand side.c. 75% in the body on the left-hand side.d. 90% in the body on the left-hand side. ____________________________________________________________________________ information from the dmv induicates the average of licensed drivers is mean- 39.7 and standard deviation of o- 12.5 years. assume that the distriubtion of drivers age is approx. normal. a. x=85b.x= 92c. x=78