Answer each question in Q&A format. Due in 8 hours

1. Respond to the following in minimum 75 words: A response variable is basically what it sounds like and that is a response. So it is what or how something responds to what is testing it. So for example if you are doing an experiment on growing a plant, and you change the different variables so like how much light and water you give them. The response variable would be how the plant responds to those changes. The independent variable would be the water and the sun light just because you can manipulate them and add as much or as little as you want to add. Treatments are basically the different levels that you can adjust the independent variable to. So basically something like the water you can adjust it and do one ounce or other times do three ounces. Then you can see how the difference affects the plant. You can see if it grows more or less depending on the amount of water the plant receives. These factor into statistics hypothesis testing because it is basis of any testing, if you do an experiment you will always have different variables, some that you can control and some that you can not control. You will always have a response variable with every experiment. 2.In minimum 200 words In what business functions, or functional areas, might managers rely on two-sample hypothesis testing and ANOVA? Provide examples of why these apply to these areas. 3. Respond to the following in minimum 75 words: Two-sample hypothesis testing is statistical analysis designed to test if there is a difference between two means from two different populations. For example, a two-sample hypothesis could be used to test if there is a difference in the mean salary between male and female doctors in the New York City area. A two-sample hypothesis test could also be used to test if the mean number of defective parts produced using assembly line A is greater than the mean number of defective parts produced using assembly line B. Similar to one-sample hypothesis tests, a one-tailed or two-tailed test of the null hypothesis can be performed in two-sample hypothesis testing as well. The two-sample hypothesis test of no difference between the mean salaries of male and female doctors in the New York City area is an example of a two-tailed test. The test of whether or not the mean number of defective parts produced on assembly line A is greater than the mean number of defective parts produced on assembly line B is an example of a one-tailed test. Analysis of variance (ANOVA) is an analysis tool used in statistics that splits an observed aggregate variability found inside a data set into two parts: systematic factors and random factors. The systematic factors have a statistical influence on the given data set, while the random factors do not. Analysts use the ANOVA test to determine the influence that independent variables have on the dependent variable in a regression study. A manager might, for example, test employees customer service from multiple departments to see if the employee from one of the departments consistently outperform the employee from the other department. 4. In Minimum 100 words. Summarize all of the above