Based on whether it is true or not determines whether we accept or reject the hypothesis. We accept true hypotheses and reject false hypotheses. The null hypothesis is the hypothesis that is claimed and that we will test against.
Making conclusions about the difference of means Video transcript - [Instructor] "Market researchers conducted a study "comparing the salaries of managers "at a large nationwide retail store.
So, pause this video and try to figure this out on your own. So first, let's think about the difference between a paired T test and a two-sample T test. In a paired T test, we're gonna construct hypotheses around a parameter for our population that will often be the mean difference.
So, we have one population, so we're talking about the paired situation right over here, and so, let's say we say, "Hey, do people run faster when they wear shorts or pants?
And then, you would calculate the difference, and then across the whole population, you could actually get that mean difference. So, the mean difference of pants minus shorts. And of course, in order to estimate that, or in order to do a hypothesis test around that, you would take a sample, and then you would calculate the sample mean of the difference of pants minus shorts, and then, you would say, "Hey," assuming the null hypothesis is true, you would construct some null hypothesis, likely that there is no, that this mean is zero, and you would say, "Hey, if the null hypothesis is true, "that this is actually equal to zero, "what's the probability that I got this result?
For example, you could be thinking about a population of men, and you could be thinking about the population of women. And you wanna compare the means between these two, say, the mean salary.
So, you have the mean salary for men and you have the mean salary for women, and what you're trying to do with the hypothesis test is try to come up with some conclusions about the mean difference between these two parameters.
So, the mean salary for men minus the mean salary for women. And our null hypothesis is usually the no-news-here hypothesis, and so in this situation, our null hypothesis is that there is no difference between these means and that our alternative hypothesis in the situation that we are looking at, because they wanna test if managers who are men have a higher average salary.
If they just wanted to test that whether managers who are men have a different salary, then our alternative hypothesis would look something like this, where the mean of men minus the mean of women is not equal to zero, but they aren't just testing to see if the means are different, they wanna see if men have a higher average salary.
So, instead of not equal zero there, we would have greater than zero for our alternative hypothesis. So, which choice is that? Well, we're clearly in a two-sample T test situation, and we wanna do the greater than, not the not-equal-to, so we are in that choice, right over there.Write the null and alternative hypothesis symbolically.
1. Discuss the process for hypothesis testing.
The average age of all patients admitted to the hospital with infectious diseases is less than 65 years of age. answer the following: 1. Write the null and alternative hypothesis symbolically and identify which hypothesis is the claim.
Observation: Suppose we perform a statistical test of the null hypothesis with α and obtain a p-value of p, thereby rejecting the null hypothesis. This does not mean that there is a 4% probability of the null hypothesis being true, i.e.
P (H 0) Develop a testable hypothesis, confidence level, and degrees of freedom. Report the required "t" critical values based on the degrees of freedom.
Report the required "t" critical values based on the degrees of freedom.
The null hypothesis, H 0 is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis. Researchers work to reject, nullify or disprove the null hypothesis.
The typical approach for testing a null hypothesis is to select a statistic based on a sample of fixed size, calculate the value of the statistic for the sample and then reject the null hypothesis if and only if the statistic falls in the critical region.
The null hypothesis, H 0 is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis.
Researchers work to reject, nullify or disprove the null hypothesis.