Hypothesis testing:
It is
usually impossible for a researcher to observe each individual in a population.
Therefore, he selects some individual from the population as sample and
collects data from the sample. He then uses the sample data to answer questions
about the population. For this purpose, he uses some statistical techniques.
Hypothesis
testing is a statistical method that uses sample data evaluate a hypothesis
about a population parameter. A hypothesis test is usually used in context of a
research study. Depending on the type of research and the type of data, the
details of the hypothesis test will change from on situation to another.
Hypothesis
testing is a formalized procedure that follows a standard series of operations.
In this way a researcher has a standardized method for evaluating the results
of his were evaluated and how conclusions were drawn.
Logic of
hypothesis testing
According to
Gravette & Wallnau the logic underlying hypothesis testing is as follows:
·
First a researcher states a hypothesis about a
population. Usually, the hypothesis concerns the value of the population mean.
For example, we might hypothesize that the mean IQ for the registered voters
Pakistan is M= 100.
·
Before a researcher actually selects a sample, he uses
the hypothesis to predict the characteristics that the sample should have. For
example, if he hypothesizes that the population mean IQ=100, then would predict
that the sample should have a mean around 100. It should be kept in mind that
the sample should be similar to the population but there is always a chance
certain amount of error.
·
Next, the researcher obtains a random sample from the
population. For example, he might select a random sample of n= 200 registered
voters to compute the mean IQ for the sample.
·
Finally, he compares the obtained sample data with the
prediction that was made from the hypothesis. If the sample mean is consistent
with the prediction, he will conclude that the hypothesis is reasonable. But if
there is big difference between the data and the prediction, he will decide
that the hypothesis is wrong.
KEY TAKEAWAYS
Speculation testing is utilized to evaluate the credibility of a theory by utilizing test information.
The test gives proof concerning the believability of the speculation, given the information.
Factual investigators test a theory by estimating and inspecting an irregular example of the populace being broke down.
How Hypothesis Testing Works
In theory testing, an investigator tests a measurable example, determined to give proof on the credibility of the invalid speculation.
Factual investigators test a speculation by estimating and looking at an irregular example of the populace being dissected. All experts utilize an irregular populace test to test two distinct speculations: the invalid theory and the elective speculation.
The invalid theory is generally a speculation of fairness between populace boundaries; e.g., an invalid theory may express that the populace mean return is equivalent to nothing. The elective theory is successfully something contrary to an invalid speculation (e.g., the populace mean return isn't equivalent to nothing). Accordingly, they are totally unrelated, and just one can be valid. Notwithstanding, one of the two theories will consistently be valid.
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