1. One step in hypothesis testing is to randomly assign members of the sample into the control group and the experimental group. What is the difference between these two groups? Randomly assigning members of a sample into the control group and the experimental group is a way to split the independent variable into two groups in order to test the dependent variable. This is done to see any changes that are made to the independent variable when the dependent variable is introduced. The difference between the two groups is the dependent variable. Both the control and experimental groups begin as equals. A true random sample would leave the two group with statistically no difference between the age, gender, or socioeconomic status, especially if those social factors would play a role in the experiment. The control group does not receive the treatment with the dependent variable. This is the only factor that differentiates the control group from the experimental group (Nolan & Heinzen, 2014). The experimental group receives the treatment or intervention of the dependent variable, or the interest of the study, which should cause a change to happen between the control group and the experimental group. 2. Why does the standard error become smaller simply by increasing the sample size? By increasing sample size, the sample is a lot closer to the population itself. In other words, larger samples give us more confidence in our conclusions (Nolan & Heinzen, 2014). Here is an example to illustrate how sample size can affect standard error: I have a very small foot (size 5 in women's). One day I decided to buy a pair boots from Target. However, they did not have the boots in my size. I checked another Target nearby and they also did not have my size. I assume that none of the Target stores in my area have this pair of boots in my size. In another scenario, I check 7 different Target stores for that same pair of boots in my size. I then assume that none of the Target stores in my area have this pair in my size. My assumption that none of the Target stores in my area have the pair of boots in my size is a lot more accurate in the second scenario than in the first because I checked more stores (sample size is greater). In the first scenario I gave up after only checking two stores, which is not enough because there were many other stores in the area that may have had the pair of boots