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Unformatted text preview: RES 342 Research and Evaluation II RES/342 Week One ONE SAMPLE HYPOTHESIS TESTING Introduction In this week, we transition from confidence intervals and interval estimates presented in RES/341 to hypothesis testing, the basis for inferential statistics. Inferential statistics means using a sample to draw a conclusion about an entire population. A test of hypothesis is a procedure to determine whether sample data provides sufficient evidence to support a position about a population. This position or claim is called the alternative or research hypothesis. It is a procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement (Lind, Marchal, & Wathen, 2005). This Week in Relation to the Course Hypothesis testing is at the heart of research. In this week, we examine and practice a procedure to perform tests of hypotheses comparing a sample mean to a population mean. In subsequent weeks, we will use the same procedures to test two or more sample means (ANOVA), non- parametric data, correlation, and regression. The Five-Step Procedure for Hypothesis Testing Step 1 State the null hypothesis equating the population parameter to a specification. The null hypothesis is always one of status quo or no difference. We call the null hypothesis H (H sub zero). It is the hypothesis that contains an equality. State the alternate hypothesis The alternate is represented as H 1 or H A (H sub one or H sub A). The alternate hypothesis is the exact opposite of the null hypothesis and represents the conclusion supported if the null is rejected. The alternate will not contain an equal sign of the population parameter. Most of the time, researchers construct tests of hypothesis with the anticipation that the null hypothesis will be rejected....
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- Spring '10