The answer depends on whether the test is one-tailed or two-tailed.One-tailed: z = 1.28 Two-tailed: z = 1.64
2.58
z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.
Z = ± 1.8119 gives a two-tailed interval of 93%
The answer will depend on whether the critical region is one-tailed or two-tailed.
The answer depends on whether the test is one-tailed or two-tailed.One-tailed: z = 1.28 Two-tailed: z = 1.64
-2.58,2.58
+2.58
2.58
1.64
The type I error is 0.0027 only when a two tailed test is used with a z-score of ±3. There are many occasions when a one-tailed test is more appropriate and with the same test would have half the Type I error. Furthermore, it is more usual for the researcher to specify the type I error first - 0.05, 0.01 or 0.001 are favourites - and to select one-or two-tailed critical region after that. It is, therefore, more likely that the Type I error is a "round" number (5%, 1% or 0.1%) while the critical z-score is not.
Whereas a t-test is used for n30, where n=sample size. n < 30 or n > 30 is not entirely arbitrary; it is intended to indicate that n must be sufficiently large to use the normal distribution. In some cases, n must be greater than 50. Note, both the t-test and the z-test can only be used if the distribution from which the sample is being drawn is a normal distribution. A z-test can be used even if the distribution is not normal (but is not severely skewed) if n>30, in which case, we can safely assume that the distribution is normal.
z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.z = 1.56 gives a 2-tailed interval for 88%.
Z = ± 1.8119 gives a two-tailed interval of 93%
The answer will depend on whether the critical region is one-tailed or two-tailed.
A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.
Each different t-distribution is defined by which of the following? @Answer found in section 4.3 The One-sample t-Test, in Statistics for Managers