Design (but not do) a test to see if genetically modified foods are different from non-genetically modified (NGM) foods. Assume you are designing a study that will analyze GM and NGM foods, and answer the following questions.
1. What will your null and alternative hypotheses be? (Hint: Ensure your null and alternative hypotheses are logical opposites. Also, be sure to specify your dependent variables; that is, what you're interested in testing. Some of these are yield per acre, drought tolerance, protein content, pest resistance, and whether GM foods are more likely to cause illness [specify the illness] than NGM foods.)
2. What significance level will you use to test this hypothesis? Why this level?
3. Would the Chi Square hypothesis test apply to this study? Why? (Hint: Chi Square is for nominal data having no presumed distribution? Are the data for your GM vs. NGM tests nominal without predetermined distribution?)
This solution conducts a hypothesis test to look at the differences between GMO and non-GMO foods by providing a null and alternative hypothesis, calculating the chi-square test statistic, comparing it to the p-value and making a decision to accept or reject the null hypothesis. All steps are shown with justifications and full formulas.