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Question: In developing the national certification exam for counselors, the test developers wanted to ensure adequate validity and reliability. For the following items, place the letter that represents the kind of validity or reliability described (match): 1. All the possible split-half correlations are calculated, and then the mean, or average, of all of these scores is obtained. 2. The test is correlated with the national comprehensive exams to ensure that the two tests are not measuring the same thing. 3. Students who are graduating from their master's degrees take the test, and, at the same time, their test scores are correlated with professor rankings of how good a student they are. 4. Student scores on the exam are correlated with how well supervisors rate them two years later. 5. Half of the test is correlated with the other half of the test. 6. In creating the test, they hypothesized that students who finished a master's degree in counseling would do significantly better than students who received a master's in psychology. Then, a study is conducted examining this hypothesis. 7. The test is given to a group of students, and then, one day later, they take the same test again. 8. In developing the test, counseling books were surveyed, and experts were contacted in an effort to create items. 9. Students take two different versions of the same test, and their scores are correlated. a. Discriminant validity b. Concurrent validity c. Content validity d. Test-retest reliability e. Predictive validity f. Construct validity g. Odd-even reliability h. Internal consistency i. Parallel or equivalent form reliability
Akash M.
3. Calculating the Pearson correlation with z-scores Imagine that a professor of psychology has two teaching assistants (TAs) who will help him grade assignments for the duration of the semester. The professor wants to make sure that he and the TAs are well calibrated with one another, so he has all three of them grade the first assignment independently. Because the professor grades every assignment on a curve, he first converts the students' scores to z-scores for each grader. The following table shows the z-scores for a population of 10 students in his class for each grader. Professor Teaching Assistant #1 Teaching Assistant #2 Student 1 1.28 0.62 1.24 Student 2 -1.55 0.85 -0.60 Student 3 -0.13 -0.98 0.39 Student 4 0.89 2.23 0.79 Student 5 -1.06 -0.53 -1.28 Student 6 0.31 0.45 0.12 Student 7 -1.51 -1.03 -2.17 Student 8 1.15 0.00 0.84 Student 9 0.58 -0.53 0.48 Student 10 0.04 -1.07 0.21 The professor is going to use the z-scores to calculate the correlation coefficient between his scores and those of his TAs. To calculate the correlation coefficient, he sums the products of the z-scores. The professor should divide this sum by . The professor constructed a table of correlation coefficients between his scores and those of his TAs. Select the correct missing correlation. Professor Teaching Assistant #1 Teaching Assistant #1 1 Teaching Assistant #2 0.91 0.41 Based on the correlation table, the professor should arrive at which of the following conclusions? The professor and TA #1 are well calibrated, but TA #2 is off. The professor and TA #2 are well calibrated, but TA #1 is off. The professor and both of his TAs are well calibrated. The two TAs are well calibrated with each other but not with the professor. The professor thinks he tends to be a harsh grader and decides to add 5 points to each student's grade before converting the scores to z-scores and computing the Pearson correlation coefficient between his grades and the two teaching assistants'. This change in the professor's scores will the correlation between the professor's scores and TA #1's and TA #2's scores.
Shyam P.
What is the relationship between the amount of time statistics students study per week and their final exam scores? The results of the survey are shown below. Time 1 8 2 4 3 3 15 Score 62 92 65 63 70 76 100 a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: H0: ? = 0 H1: ? ≠ 0 The p-value is: (Round to four decimal places) c. Use a level of significance of ̑̑ = 0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically significant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful. There is statistically insignificant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. There is statistically insignificant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. d. r² = (Round to two decimal places) e. Interpret r² : 84% of all students will receive the average score on the final exam. There is a large variation in the final exam scores that students receive, but if you only look at students who spend a fixed amount of time studying per week, this variation on average is reduced by 84%. Given any group that spends a fixed amount of time studying per week, 84% of all of those students will receive the predicted score on the final exam. There is a 84% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. f. The equation of the linear regression line is: ŷ = + x (Please show your answers to two decimal places) g. Use the model to predict the final exam score for a student who spends 6 hours per week studying. Final exam score = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: For every additional hour per week students spend studying, they tend to score on averge 2.82 higher on the final exam. As x goes up, y goes up. The slope has no practical meaning since you cannot predict what any individual student will score on the final. i. Interpret the y-intercept in the context of the question: The average final exam score is predicted to be 61.
Ariana N.
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