# Logic of hypothesis testing

If a sample of rat pups which were exposed to prenatal alcohol has a birth weight "near" 18 grams we conclude that the treatement does not have an effect. We do this by obtaining a random sample from the population.

Also, suppose that we know that the mean birth weight of the population of untreated lab rats is 18 grams. NOTE: We do not conclude it is right, but reasonable! At birth, we measure the weight of the sample of newborn rats.

### Logic of hypothesis testing

Third Step: Gather Data. If our sample of rat pups has a birth weight "far" from 18 grams we conclude that the treatement does have an effect. This is denoted The Alternative Hypothesis H1. Gather Data: We obtain a random sample from the population. More on this later. This hypothesis states that the treatment does have an effect. The four steps for conducting a hypothesis test are introduced and you get to apply them for hypothesis tests for a population mean as well as population proportion. We do this by obtaining a random sample from the population. If a sample of rat pups which were exposed to prenatal alcohol has a birth weight "near" 18 grams we conclude that the treatement does not have an effect. Formally: we reject the null hypothesis. We will introduce the three kinds of difference in means test and apply them to various business applications.

This hypothesis states that the treatment has no effect. Towards the close of module we start introducing the concept of Hypothesis Testing. DIST and T.

### Test of significance

Now we gather data. This is the third course in the specialization "Business Statistics and Analysis" and the course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing. If our sample of rat pups has a birth weight "far" from 18 grams we conclude that the treatement does have an effect. Also, suppose that we know that the mean birth weight of the population of untreated lab rats is 18 grams. Usually the hypothesis concerns the value of a population parameter. This is denoted The Alternative Hypothesis H1. If the data are consistent with the hypothesis we conclude that the hypothesis is reasonable. We do this by obtaining a random sample from the population. State the Hypothesis: We state a hypothesis guess about a population. Example: We compare the observed mean birth weight with the hypothesized value, under the null hypothesis, of 18 grams. Here are the two opposing hypotheses: The Null Hypothesis Ho. We will also introduce the Excel dialog box to conduct such hypothesis tests. The weights, in grams, are shown in the table. For our example, we formally state: The null hypothesis Ho is that prenatal exposure to alcohol has no effect on the birth weight for the population of lab rats.

This is denoted The Alternative Hypothesis H1. This is the third course in the specialization "Business Statistics and Analysis" and the course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing.

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