only the mean of the scores is affected by the independent variable, not thevarianceB.Three or more random samples (each tested once) derived by:1.Three or more different samples from same population (looking to see ifpopulational differences due to treatment or chance)C.Data values1.Sample values known (mean, standard deviation)2.Populational values (mean, standard deviation) not knownII.Diagramming your research (shows the whole logic and process of hypothesis testing)a.Draw a picture of your research design (see diagramming your research handout).b.There are always two explanations (i.e. hypotheses) of your research results, thewording of which depends on whether the research question is directional (one-tailed)or non-directional (two-tailed). State them as logical opposites.c.For statistical testing, ignore the alternative hypothesis and focus on the null hypothesis,since the null hypothesis claims that the research results happened by chance throughsampling error.d.Assuming that the null is true (i.e. that the research results occurred by chance throughsampling error) allows one to do a probability calculation (i.e. all statistical tests arenothing more than calculating the probability of getting your research results by chancethrough sampling error).e.Observe that there are two outcomes which may occur from the results of theprobability calculation (high or low probability of getting your research results bychance, depending on the alpha (α) level).f.Each outcome will lead to a decision about the null hypothesis, whether the null isprobably true (i.e. we then accept the null to be true) or probably not true (i.e. we thenreject the null as false).III.HypothesesA.One-tailed (all F ratio’s are one-tailed)1.Alternative hypothesis (H1): The independent variable does make a difference inperformance between the groups.