For Hypthesis

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To truly understand what is going on, we should read through and work through several examples.If we know about the ideas behind hypothesis testing and see an overview of the method, then the next step is to see an example.Further, suppose that we know that the population standard deviation of everyone who is 17 years old is 0.6 degrees.

To truly understand what is going on, we should read through and work through several examples.If we know about the ideas behind hypothesis testing and see an overview of the method, then the next step is to see an example.Further, suppose that we know that the population standard deviation of everyone who is 17 years old is 0.6 degrees.

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To test this “hypothesis,” we record marks of say 30 students (sample) from the entire student population of the school (say 300) and calculate the mean of that sample.

We can then compare the (calculated) sample mean to the (reported) population mean and attempt to confirm the hypothesis.

If the null hypothesis is accepted or the statistical test indicates that the population mean is 12 minutes, then the alternative hypothesis is rejected. The null hypothesis, also known as the conjecture, assumes that any kind of difference or significance you see in a set of data is due to chance.

The opposite of the null hypothesis is known as the alternative hypothesis.

The statistical evidence shows that either a rare event has occurred, or that the average temperature of those who are 17 years old is, in fact, greater than 98.6 degrees.

A null hypothesis is a type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations.Statistical hypotheses are tested using a four-step process.The first step is for the analyst to state the two hypotheses so that only one can be right.Therefore, the null hypothesis would be stated as, "The population mean is equal to 12 minutes." Conversely, the alternative hypothesis is the hypothesis that is accepted if the null hypothesis is rejected.Hypothesis testing allows a mathematical model to validate or reject a null hypothesis within a certain confidence level.The fourth and final step is to analyze the results and either accept or reject the null hypothesis.Here is a simple example: A school principal reports that students in her school score an average of 7 out of 10 in exams.We take a random sample of annual returns of the mutual fund for, say, five years (sample) and calculate its mean.We then compare the (calculated) sample mean to the (claimed) population mean to verify the hypothesis.The following shows a worked out example of a hypothesis test.Suppose that a doctor claims that those who are 17 years old have an average body temperature that is higher than the commonly accepted average human temperature of 98.6 degrees Fahrenheit.

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