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Does the p-value depend on the alternative hypothesis?
Frankly, the alternative hypothesis is unnecessary. It is not used in the computation of p-values or for determining statistical significance. The only practical use for the alternative hypothesis that I can see is in determining the power of a test.
What does a simple hypothesis mean?
Simple hypotheses are ones which give probabilities to potential observations. The contrast here is with complex hypotheses, also known as models, which are sets of simple hypotheses such that knowing that some member of the set is true (but not which) is insufficient to specify probabilities of data points.
How is the p value of a hypothesis determined?
The P -value approach involves determining “likely” or “unlikely” by determining the probability — assuming the null hypothesis were true — of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed. If the P -value is small, say less than (or equal to) α, then it is “unlikely.”
When does a hypothesis become a composite hypothesis?
Composite hypothesis, on the other hand, refers to the hypothesis that does not stand to be simple. For instance, if it is assumed that and or and then such hypothesis tends to become a composite hypothesis. This is because, in either of the cases, the exact distribution is not known.
Which is the t statistic for the hypothesis test?
Again, to conduct the hypothesis test for the population mean μ, we use the t -statistic t ∗ = x ¯ − μ s / n which follows a t -distribution with n – 1 degrees of freedom.
What happens if the p value is greater than α?
And, if the P -value is greater than α, then the null hypothesis is not rejected. Specifically, the four steps involved in using the P -value approach to conducting any hypothesis test are: Specify the null and alternative hypotheses. Using the sample data and assuming the null hypothesis is true, calculate the value of the test statistic.