Question

A researcher records the number of words recalled by students presented with a list of words for one minute. In one group, students were presented with the list of words in color and for the other group, the words were presented in black and white. Test to see if there are differences in the number of words recalled, using alpha = .05 and four steps. Also calculate and interpret effect size and explained variance if appropriate. Before: 7 4 7 7 7 6 After: 5 6 5 6 5 5

A) Step 1: Collect data, Step 2: Calculate the p-value, Step 3: Reject or fail to reject the null hypothesis, Step 4: Calculate the effect size

B) Step 1: Design the experiment, Step 2: Choose the alpha level, Step 3: Report the results, Step 4: Interpret the effect size

C) Step 1: Hypothesize, Step 2: Conduct the experiment, Step 3: Analyze the data, Step 4: Draw conclusions

D) Step 1: Recruit participants, Step 2: Calculate the standard error, Step 3: Prepare a research paper, Step 4: Discuss potential limitations

Answer 1

A researcher is testing if there are differences in the number of words recalled by students based on the color of the words. Steps for hypothesis testing, including null and alternative hypotheses, test statistics, p-values, and types of errors, are explained.

Step-by-step explanation:

A) The appropriate null hypothesis for this study is that there is no difference in the number of words recalled between the two groups of students.

B) The appropriate alternative hypothesis is that there is a difference in the number of words recalled between the two groups of students.

C) The random variable, P', represents the difference in the number of words recalled between the two groups of students.

D) To calculate the test statistic, subtract the mean number of words recalled by the black and white group from the mean number of words recalled by the color group, and divide it by the standard error of the difference.

E) The p-value is calculated by comparing the test statistic to the appropriate distribution (usually a t-distribution or z-distribution), and determining the probability of obtaining a test statistic as extreme as the one observed if the null hypothesis is true.

F) At the 5 percent level of decision, if the p-value is less than 0.05, we reject the null hypothesis. If the p-value is greater than or equal to 0.05, we fail to reject the null hypothesis.

G) Type I error is the probability of incorrectly rejecting the null hypothesis when it is actually true.

H) Type II error is the probability of failing to reject the null hypothesis when it is actually false.