1.00
It is true because the distribution is symmetrical about Z=0.
no, z score can be negative but a probability is a always positive between 0 and 1.
0.97
z = (80 - 100)/20 = -20/20 = -1 Look up a table of z-scores: Probability = 15.87%
P(0 < Z < z) = 0.3770 is the same as looking at P(Z < z) = 0.8770 because the other half of the curve (anything less than 0) has probability of 0.5. Now this is a problem of just looking it up from the table. The table gives a value z = 1.16 for the probability of 0.8770. So P(0 < Z < 1.16) = 0.3770.
The probability is 0.664
It is true because the distribution is symmetrical about Z=0.
no, z score can be negative but a probability is a always positive between 0 and 1.
-0.92
It is 0.0146
True. Due to the symmetry of the normal distribution.
0.97
z = (80 - 100)/20 = -20/20 = -1 Look up a table of z-scores: Probability = 15.87%
The area under the normal curve between z = -1.0 and z = -2.0 can be found using the standard normal distribution table or a calculator. The area corresponds to the probability of a z-score falling within that range. For z = -1.0, the cumulative probability is approximately 0.1587, and for z = -2.0, it is about 0.0228. Therefore, the area between these two z-scores is approximately 0.1587 - 0.0228 = 0.1359, or 13.59%.
P(0 < Z < z) = 0.3770 is the same as looking at P(Z < z) = 0.8770 because the other half of the curve (anything less than 0) has probability of 0.5. Now this is a problem of just looking it up from the table. The table gives a value z = 1.16 for the probability of 0.8770. So P(0 < Z < 1.16) = 0.3770.
P(0 < z < 2.53) refers to the probability that a standard normal random variable (z) falls between 0 and 2.53. To find this probability, you would typically look up the z-scores in a standard normal distribution table or use a calculator. The cumulative probability for z = 2.53 is approximately 0.994, and for z = 0, it is 0.5. Therefore, P(0 < z < 2.53) is approximately 0.994 - 0.5 = 0.494.
The probability is 0.005012, approx.