0
For a normal distribution what is the proportion in the tail beyond z -1.50?
Wiki User
∙ 7y agoWant this question answered?
Be notified when an answer is posted
Add your answer:
Earn +20 pts
Can a standard deviation be greater than its mean?
Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.
What does positive skewness signify in normal distribution?
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'.
What is skewness how would you find it in a non symmetrical distribution?
Skewness is a measure of the asymmetry in a distribution. In a non-symmetrical distribution, skewness can be calculated using a formula that considers the deviation of each data point from the mean. A positive skewness indicates a longer tail on the right side of the distribution, while a negative skewness indicates a longer tail on the left side.
What is coefficient of skewness in a variable concentration?
A measure of skewness is Pearson's Coefficient of Skew. It is defined as: Pearson's Coefficient = 3(mean - median)/ standard deviation The coefficient is positive when the median is less than the mean and in that case the tail of the distribution is skewed to the right (notionally the positive section of a cartesian frame). When the median is more than the mean, the cofficient is negative and the tail of the distribution is skewed in the left direction i.e. it is longer on the left side than on the right.
How do you derive Moment generating function of Pareto distribution?
The moment generating function for any real valued probability distribution is the expected value of e^tX provided that the expectation exists.For the Type I Pareto distribution with tail index a, this isa*[-x(m)t)^a*Gamma[-a, -x(m)t)] for t < 0, where x(m) is the scale parameter and represents the least possible positive value of X.
What is the proportion of a normal distribution is located in the tail beyond a z score of z equals 1.00?
It is 0.158655, approx.
What proportion of a normal distribution is located in the tail beyond a z-score if z equals -1.50?
0.0668 or about 1/15
What proportion of a normal distribution is located in the tail beyond a z score of z equals 1.00?
It is 0.158655 or 0.159 approx.is the anwer 0.8413, -0.3413, -0.1587, 0.1587
What percentage of a normal distribution is located in the tail beyond a z-score of z - 1.20?
11.51% of the distribution.
What percentage of a normal distribution is located in the tail beyond z equals 2.00?
2.27%
What percent of a normal distribution is located in the tail beyond z equals 2.00?
2.27
Can a standard deviation be greater than its mean?
Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.
Describe the sampling distribution model for the sample proportion by naming the model and telling its mean and standard deviation?
it is the test one tail
Why two tail of normal distribution do not touch the horizontal axis?
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.
What is the proportion of data that is in the tail for a z-score of - 1.17.?
It is .121
A normal distribution has a mean of 60 and a standard deviation of 20 for each What scores indicate weather the tail of the distribution is to the left or the right of the score and?
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
Find the Z score location of vertical line that separate a normal distribution as described in each of the followinf 20 percent in the tail on the left?
Z = -0.8416
