![]() Because the samples drawn from any population vary, you can never be positive of your finding, but by following generally accepted hypothesis testing procedures, you can limit the uncertainty of your results.Īs you will learn in this chapter, you need to choose between two statements about the population. Hypothesis testing allows you to find out, in a formal manner, if the sample supports your idea about the population. While you usually have good reasons to think it is true, and you often hope that it is true, you need to show that the sample data support your idea. In estimation, you are answering the question, “What is the population like?” While in hypothesis testing you are answering the question, “Is the population like this or not?”Ī hypothesis is essentially an idea about the population that you think might be true, but which you cannot prove to be true. Though the mathematics of hypothesis testing is very much like the mathematics used in interval estimation, the inference being made is quite different. It is different from estimation because you start a hypothesis test with some idea of what the population is like and then test to see if the sample supports your idea. Hypothesis testing is the other widely used form of inferential statistics.
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