Subheadings (12)

1. The offender population which the treatment program is designed to serve.
2. How the treatment addresses risk and protective factors and/or special needs of offenders.
3. The service providers and team members that should be involved in the treatment.
4. How to address any potential complications with implementation of the program.
5. A case study example of the program in practice, (can be fictional, but must be realistic and credible)
6. Conclude by summarizing how your selected approach can utilize a case management approach to provide a comprehensive individualized treatment program.
7. The offender population which the treatment program is designed to serve.
8. How the treatment addresses risk and protective factors and/or special needs of offenders.
9. The service providers and team members that should be involved in the treatment.
10. How to address any potential complications with implementation of the program.
11. A case study example of the program in practice, (can be fictional, but must be realistic and credible)
12. Conclude by summarizing how your selected approach can utilize a case management approach to provide a comprehensive individualized treatment program.

1. Which statement is NOT true regarding the slope of a regression equation?

	a.	The slope quantifies the steepness of the line.
	b.	If the slope is negative, Y tends to decrease as X tends to decrease.
	c.	If the slope is positive, Y tends to increase as X tends to increase.
	d.	None of the above, all are true.

Question 2

1. The scale of the correlation coefficient is:

	a.	nominal
	b.	interval
	c.	ordinal
	d.	ratio

Question 3

1. A fellow researcher tells you that she got ap calculated of .04 from an inferential test she conducted. She asks you if her results are statistically significant. The most informed response would be:

	a.	Yes, because the probability of obtaining your sample statistic was less than .05.
	b.	Yes, because your alpha level was greater than your obtained p calculated.
	c.	No,because the probability of obtaining your sample statistic was greater than .05.
	d.	No, because your alpha level was greater than your obtained p calculated.
	e.	It depends, what did you set your probability of Type I error to be?

Question 4

1. Use the following scenario to answer the next 2 questions.

Working a full-time job and taking classes at night can be very stressful at times. Recently a study was conducted to determine whether the amount of sleep taken the night before a test differed for UNT graduate students with full-time jobs as compared to UNT graduate students in general, and you expect that graduate students with full-time jobs get less sleep. The data collected were as follows. Assume that we know the general population of UNT graduate students sleep 7 hours the night before a test and that this distribution is normal. The standard deviation around this population mean is 2.5 hours. The study’s sample of 25 UNT graduate students with full-time jobs slept 6 hours before a test with a standard deviation of 5. Assume alpha = .05. ROUND ALL CALCULATIONS TO TWO DECIMAL PLACES.

What is the calculated Z-test value?

	a.	-.2
	b.	-.4
	c.	-1.0
	d.	-2.0
	e.	none of the above

Question 5

1. What is thep calculated (probability) for your sample results?

	a.	.0114
	b.	.3446
	c.	.0228
	d.	.1554
	e.	.1723

Question 6

1. Statistical significance testing (null hypothesis tests) depends on the assumption that:

	a.	you have a large sample size.
	b.	the null hypothesis is true in the population.
	c.	you have a low risk if Type I error.
	d.	the alternative hypothesis cannot be proven true.
	e.	none of the above

Question 7

1. A statistically significant result means that, given the assumptions of the test, you have a(n):

	a.	replicable result.
	b.	important result
	c.	unlikely result
	d.	unimportant result

Question 8

1. In the process of testing a null hypothesis, which of the following should precede the others.

	a.	Computing the test statistic.
	b.	Deciding whether to reject Ho.
	c.	Determining your conclusion regarding group differences.
	d.	Establishing the criterion for rejecting.

Question 9

1. Which of the following isnot true about Pearson r and Spearman rho?

	a.	r ranges from -1 to +1.
	b.	When Spearman rho = 1.00, then Pearson r will always be 1.00.
	c.	When Pearson r = 1.00, then Spearman rho will always be 1.00.
	d.	r and rho cannot be compared without more information.

Question 10

1. Which alpha level below corresponds to the most risk of Type I error?

	a.	alpha = .10
	b.	alpha = .05
	c.	alpha = .01
	d.	alpha = .001

Question 11

1. Which of the following is an example of an alternative hypothesis?

	a.	Exercising 30 minutes a day for 2 weeks does not decrease heart rate by 10%.
	b.	Taking 500mg of ibuprofen within 20 minutes of onset will decrease headache pain.
	c.	Studying more than 5 hours for a statistics final does not impact your grade.
	d.	There is no difference between the mean self-esteem scores of mean and women athletes at UNT.

Question 12

1. Graphic r-Q1 of 2

	a.	.8
	b.	-.8
	c.	-1.0
	d.	.7
	e.	.6

Question 13

1. If we now add thetwo plotted points marked with (g), which of the following is not true?

	a.	The line of best fit will come closer to catching all points.
	b.	r will increase in magnitude.
	c.	r will approach its numerical limit.
	d.	None of the above; all are true.

Question 14

1. The primary goal of inferential statistics is to:

	a.	describe characteristics of samples based on population parameters.
	b.	suggest characteristics of populations based on sample statistics.
	c.	find exact values for population parameters with our sample statistics.
	d.	find exact values for sample statistics given estimated population parameters.
	e.	drive graduate students “batty”.

Question 15

1. Use the following data forthe next four questions.

	X	Y
Linda	3	-2
Jane	4	0
Dean	5	2
Lesley	6	8

1. Which statement is true?

	a.	Pearson r is positive.
	b.	Pearson r is positively skewed.
	c.	Pearson r = 1.
	d.	Pearson r = Spearman rho.
	e.	None of the above, all are false.

Question 16

1. If we change Lesley’s X score to 4, which statement is true?

	a.	Pearson r becomes larger.
	b.	Spearman rho becomes smaller.
	c.	Spearman rho = Pearson r.
	d.	Pearson r becomes negatively skewed.
	e.	None of the above.

Question 17

1. Now that we have changed Lesley’s X score to 4, if we change Linda’s X score to -20 which statement is true?

	a.	r is negative.
	b.	r becomes smaller.
	c.	rho becomes smaller.
	d.	rho = r.
	e.	None of the above.

Question 18

1. On theoriginal data set, if we change Lesley’s Y score (not X) to 4, which of the following is true?

	a.	r = rho
	b.	r is less than rho
	c.	r is greater than rho
	d.	Not enough information to determine.

Question 19

1. Standard error is the standard deviation of a sampling distribution. The larger the standard error, the greater risk of _____________ error.

	a.	sampling
	b.	Type I
	c.	Type II
	d.	Type III
	e.	none of the above

Question 20

1. Which of the following isnot true of Pearson r and COV?

	a.	r and COV always have the same sign.
	b.	r is the COV with the impact of SD of X and SD of Y removed.
	c.	r has minimum and maximum limits while COV does not.
	d.	r = COV only when the SDs of both variables are 1.
	e.	None of the above are false, all are true.

Question 21

1. Given r = .8 and ap calculated of .6, when we test the null hypothesis that r = 0, we can say that:

	a.	there is an 80% probability of obtaining at least r = .8 from any random sample, if the r should have been 0.
	b.	there is a 60% probability of obtaining at least r = .8 from any random sample, if the r should have been 0.
	c.	there is a 60% probability of not obtaining at least r = .8 from any random sample, if the r should have been 0.
	d.	there is an 80% probability of not obtaining at least r = .8 from any random sample, if the r should have been 0.

Question 22

1. Which of the following is true regarding weak correlation coefficients?

	a.	They indicate a slight causation between variables.
	b.	They are found only with Pearson r coefficients.
	c.	They may be the result of restricted range for one of the variables.
	d.	They are rarely found in social science research.
	e.	They account for large amounts of dependent variable variability.

Question 23

1. A Pearson r of .70 is how much stronger than a Pearson r of .00 in terms of shared variance between the two variables?

	a.	30%
	b.	40%
	c.	49%
	d.	70%
	e.	None of the above

Question 24

1. In hypothesis testing, if we found a statistically significant difference between the means of two groups, then we:

	a.	rejected the null.
	b.	failed to reject the null.
	c.	committed Type I error.
	d.	committed Type II error.
	e.	none of the above

Question 25

1. When choosing a non-directional hypothesis, we:

	a.	are choosing a one-tailed test.
	b.	decrease the likelihood of Type II error.
	c.	increase the likelihood of Type I error.
	d.	decrease the likelihood of statistical significance.
	e.	none of the above

Question 26

1. As a special education researcher, you know that easy distractibility and diminished attention at school have been strongly correlated with low scores on certain tests of sensory integration. A child is found to have trouble paying attention in his classes. The school counselor asks for sensory integration therapy to remediate the attention problem. Should the therapist provide therapy right away?

	a.	Yes, because the strong correlation proves that therapy which improves sensory integration will definitely improve attention.
	b.	No, because therapy caseloads in public schools are high and this child s problems are relatively minor.
	c.	No, because a strong correlation doesn t mean that one condition necessarily causes the other; more investigation is needed to determine the possible causes of the child s distractibility.
	d.	Yes, because the school administrators are in favor of the therapy.

Question 27

1. Marcela conducted a study on SAT and GRE scores and calculated the Pearson r correlation between these scores for a sample of graduate students. Which correlation coefficient is least likely to reflect the relationship between these variables?

	a.	-1.0
	b.	-0.1
	c.	1.4
	d.	1.0
	e.	None of the above, all are equally plausible

Question 28

1. The bivariate reference point that is analogous to the univariate mean is called the:

	a.	covariance.
	b.	correlation.
	c.	coordinate.
	d.	centroid.

Question 29

1. In a regression linear equation for one predictor and a dependent variable, in which of the following scenarios will thea weight always be 0?

	a.	When the SDs of both variables are the same.
	b.	When the means of both variables are the same.
	c.	When the SDs of both variables are 0.
	d.	When the variables are in Z score form.
	e.	None of the above

Question 30

1. I am more informed of basic statistical practices now than when I began this class, and I am thusly truly grateful.

	a.	True
	b.	False
	c.	I don’t know because I think this is somehow a trick question
	d.	Maybe
	e.	It depends