Contents
What does a negative z-test statistic mean?
A negative z-score reveals the raw score is below the mean average. For example, if a z-score is equal to -2, it is 2 standard deviations below the mean. Another way to interpret z-scores is by creating a standard normal distribution (also known as the z-score distribution or probability distribution).
Can z-test statistics be negative?
A z-score, or z-statistic, is a number representing how many standard deviations above or below the mean population the score derived from a z-test is. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
Can z-test be two-tailed?
The level of significance which is selected in Step 1 (e.g., α =0.05) dictates the critical value. For example, in an upper tailed Z test, if α =0.05 then the critical value is Z=1.645….Hypothesis Testing: Upper-, Lower, and Two Tailed Tests.
| Two-Tailed Test | |
|---|---|
| α | Z |
| 0.10 | 1.645 |
| 0.05 | 1.960 |
| 0.010 | 2.576 |
How to perform the two proportion z test?
We will perform the two proportion z-test with the following hypotheses: 1 H0: π1 = π2 (the two population proportions are equal) 2 H1: π1 ≠ π2 (the two population proportions are not equal) More
What is rejection value for two tailed z test?
Recall that the rejection regions for a two tailed test with alpha set to .05 is any value above 1.96 OR any value below – 1.96. Because 1.825 is not above 1.96 or below -1.96, it is NOT in the rejection region. Therefore, this result is NOT significant.
Which is the null hypothesis in two proportion z-test?
A two proportion z-test always uses the following null hypothesis: H0: μ1 = μ2 (the two population proportions are equal) The alternative hypothesis can be either two-tailed, left-tailed, or right-tailed: H1 (two-tailed): π1 ≠ π2 (the two population proportions are not equal)
What is the critical value for upper tailed z test?
The level of significance which is selected in Step 1 (e.g., α =0.05) dictates the critical value. For example, in an upper tailed Z test, if α =0.05 then the critical value is Z=1.645. The following figures illustrate the rejection regions defined by the decision rule for upper-, lower- and two-tailed Z tests with α=0.05.