Question

• Hypothesis testing is a set of core analysis tools used to answer questions about the characteristics of a population. The process involves a number of steps, varying from five to ten depending upon the author of the text being used. What are these steps and why is it so important to follow and explicitly state each step in the process? In your responses discuss the properties of hypotheses, the importance and meaning of the level of significance and the various kinds of tests we might choose from and why.
• One and Two sample hypothesis tests (see week five for the two sample tests) are either comparing a sample to a standard value or comparing to samples to each other. Thanks to the CLT and the empirical rule we can usually trust the results

Answer 1

Hypothesis testing is a set of core analysis tools used to answer questions about the characteristics of a population. The process involves a number of steps, varying from five to ten depending upon the author of the text being used. What are these steps and why is it so important to follow and explicitly state each step in the process? In your responses discuss the properties of hypotheses, the importance and meaning of the level of significance and the various kinds of tests we might choose from and why.

Steps in the testing hypothesis are: Establish a null and an alternative hypothesis is to identify what is being tested and if the hypothesis is one-tailed or two-tailed. Determine the appropriate statistical test, determine the type, number, and level of data and statistics used such as mean, proportion. Set the value of alpha which is the probability of committing a type 1 error rate. Establish the decision rule use the alpha and the test statistic and the critical values will be determined. Gather sample data, implement or construct surveys, focus groups etc.… Analyze the data and calculate. Reach a statistical conclusion by using step 4 and step 6 to draw a statistical conclusion. Make a business decision a rejected null hypothesis or fail to reject the null hypothesis. It is important to follow these steps because it estimates two equally selected statements about the population to determine which statement is best supported by the sample data.