T-test:Use in directional vs. nondirectional hypothesis test
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Discuss how a t test can be employed in hypothesis testing by the use of directional vs. nondirectional hypotheses. Discuss types of research where using the t statistic may be an appropriate alternative to using a z-score.
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Discuss how t test can be employed in hypothesis testing by the use of directional vs. non-directional hypotheses.
A t- test assumes that the population is normally distributed and that the sampling is done randomly from the population. It uses student's t- distribution, which is also a bell-shaped curve like the normal distribution. But there are many student's t- curves depending upon the degrees of freedom. So, to read the p- value for a given t- score, or to get the critical t- score, we need to use the degrees of freedom.
A t- test can be directional or non-directional.
The hypotheses for a non-directional t- test are as below:
Ho: μ = some number and Ha: μ ≠ some number
The hypotheses for a directional (lower-tailed) t- test are as below:
Ho: μ ≥ some number and Ha: μ < some number
The hypotheses for a directional (upper-tailed) t- test are as below:
Ho: μ ≤ some number and Ha: μ > some number
Here is an example of t non-directional t- test:
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