For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.
IQ is distributed normally, with a mean of 100 and a standard deviation of 15. The z-score of 100 is therefore:(value-mean)*standard deviation= (100-100)*15= 0More generally, a raw score that is equivalent to the mean of a normal distribution will always have a z-score of 0.
z-score of a value=(that value minus the mean)/(standard deviation). So a z-score of -1.5 means that a value is 1.5 standard deviations below the mean.
The z-score must be 1.87: the probability cannot have that value!
p (z<0)
Assume the z-score is relative to zero score. In simple terms, assume that we have 0 < z < z0, where z0 is the arbitrary value. Then, a negative z-score can be greater than a positive z-score (yes). How? Determine the probability of P(-2 < z < 0) and P(0 < z < 1). Then, by checking the z-value table, you should get: P(-2 < z < 0) ≈ 0.47725 P(0 < z < 1) ≈ 0.341345
1.41
For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.
no, z score can be negative but a probability is a always positive between 0 and 1.
Yes. However, because the distribution is symmetric about 0, some tables give only positive values for z.
z-score of a value=(that value minus the mean)/(standard deviation). So if a value has a negative z-score, then it is below the mean.
z-score of a value=(that value minus the mean)/(standard deviation)
z-score of a value=(that value minus the mean)/(standard deviation)
z-score of a value=(that value minus the mean)/(standard deviation)
In a standard normal distribution curve, one half of the area is .5 (or 50%). 0 is the middle value of the z-score. So, for an area of .7704, z must be negative. Also, the area from 0 to z (which is negative) must be equal to .2704. From the normal probability table, this value is -0.74 Therefore, the z-score for the area equals 0.7704 is -0.74
Answer: 0 The z score is the value of the random variable associated with the standardized normal distribution (mean = 0, standard deviation =1). Now, the median and the mean of a normal distribution are the same. The 50 percentile z score = the median = mean = 0.
A negative z score is a value that is less than the mean value.