Five Step Hypothesis

5 Step Hypothesis Test

Hypothesis testing proves or disproves the data results of the research question. Normally an error of 5% or 1% exists when making an accurate assessment based on statistical data. Researchers use five basic steps to determine rather to accept or reject the theory and answer any research question using statistical data. The first step requires the researcher, Team B to state a research question that identifies a population of interest. Team B hypothesis suggests that obesity occurs in one of three children due to certain health factors. For this statement the population consists of obese children. The second step of hypothesis testing is a two part step which first requires Team B to specify the question in terms of null hypothesis and alternative hypothesis. This is accomplished by formulating a testable hypothesis. The second part requires Team B to assign a significance level to the hypothesis. The third step requires Team B to calculate the test statistic similar to the parameter assigned to the null hypothesis. Often the parameter µ defines the null hypothesis, so the statistics computed in Team B’s data set is similar to the mean and the standard deviation (s). The fourth step calculates the value assigned to the probability (often called the p-value) which is the probability of the test statistic. The probability value computed in this step is compared with the significance level selected in step 2, this step is the decision making step. The final step final step illustrates the results and states accurate statistical conclusions. The conclusions state two statements detailing the results of the null hypothesis and the results of the alternative hypothesis. The first statement suggests whether to accept or reject the null hypothesis and also states the value of alpha or p-value for the test statistic. The second statement answers the research question developed in the first step....