Explain what you know about hypothesis and hypothesis testing. Describe the five-step hypothesis-testing procedure? Discuss the concepts of Type I and Type II Errors? How do they relate to hypothesis testing?

The first step of the five-step hypothesis-testing procedure involves stating the null and alternative hypotheses. The second step involves selecting a level of significance. In the third step, one must quote the decision rule. The fourth step involves calculating the value of the test statistic. Lastly, the fifth step involves stating the conclusion.

A type I error is sometimes referred to as an ‘alpha error’. It is essentially a false positive and takes places when one rejects the null hypothesis when it is actually true. From another perspective, one makes a type I error when there is an acceptance of the alternative hypothesis when the results are the result of chance. One may decrease the probability of a type I error by selecting a smaller value of alpha to utilize in the decision of whether or not to reject a null hypothesis. A type II error is also referred to as a ‘beta error’. It is essentially a false negative and takes place when one doesn’t reject the null hypothesis when it should. This takes place when one does not accept a true alternative hypothesis due to the fact that there may not be sufficient power (power = 1 - beta). One may decrease the probability of a type II error by increasing the sizes of the sample.

What is the relationship between deductive and inductive arguments? Why are both types valuable in research? Provide examples of each type, illustrating benefits of their usage.

Both inductive and deductive arguments fall under the category of logical reasoning/argument. These can be considered as methods to establish the validity of a position. They may be deemed as argumentation methods, but they are more valuable. Both inductive and deductive lines of inquiry are extremely valuable in research due to their capacity to...

The first step of the five-step hypothesis-testing procedure involves stating the null and alternative hypotheses. The second step involves selecting a level of significance. In the third step, one must quote the decision rule. The fourth step involves calculating the value of the test statistic. Lastly, the fifth step involves stating the conclusion.

A type I error is sometimes referred to as an ‘alpha error’. It is essentially a false positive and takes places when one rejects the null hypothesis when it is actually true. From another perspective, one makes a type I error when there is an acceptance of the alternative hypothesis when the results are the result of chance. One may decrease the probability of a type I error by selecting a smaller value of alpha to utilize in the decision of whether or not to reject a null hypothesis. A type II error is also referred to as a ‘beta error’. It is essentially a false negative and takes place when one doesn’t reject the null hypothesis when it should. This takes place when one does not accept a true alternative hypothesis due to the fact that there may not be sufficient power (power = 1 - beta). One may decrease the probability of a type II error by increasing the sizes of the sample.

What is the relationship between deductive and inductive arguments? Why are both types valuable in research? Provide examples of each type, illustrating benefits of their usage.

Both inductive and deductive arguments fall under the category of logical reasoning/argument. These can be considered as methods to establish the validity of a position. They may be deemed as argumentation methods, but they are more valuable. Both inductive and deductive lines of inquiry are extremely valuable in research due to their capacity to...