Research Methods for the Behavioral Sciences (MindTap Course List)
6th Edition
ISBN: 9781337613316
Author: Frederick J Gravetter, Lori-Ann B. Forzano
Publisher: Cengage Learning
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Textbook Question
Chapter 14, Problem 3E
Traditional statistics (means, variances, and hypothesis tests) are not used to evaluate the results from a single-case study. Explain how the results are evaluated.
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Chapter 14 Solutions
Research Methods for the Behavioral Sciences (MindTap Course List)
Ch. 14.1 - Describe the goal of single-case research and...Ch. 14.1 - Identify the basic elements of a single-case...Ch. 14.2 - Describe the purpose of a phase in a single-case...Ch. 14.2 - Prob. 4LOCh. 14.3 - Describe the structure of an ABAB reversal design...Ch. 14.3 - Identify the strengths and weaknesses of an ABAB...Ch. 14.3 - Explain the circumstances in which an ABAB...Ch. 14.4 - Describe the structure of a multiple-baseline...Ch. 14.4 - Identity and describe the component-analysis...Ch. 14.4 - Identify the strengths and weaknesses of a...
Ch. 14.5 - Identify the general advantages and disadvantages...Ch. 14 - Prob. 1ECh. 14 - Prob. 2ECh. 14 - Traditional statistics (means, variances, and...Ch. 14 - Prob. 4ECh. 14 - Prob. 5ECh. 14 - Prob. 6ECh. 14 - What pattern of results is needed to provide...Ch. 14 - Identify the four phases that make up an ABAB...Ch. 14 - In general, how does a phase-change design like...Ch. 14 - Explain why an ABAB reversal design is...Ch. 14 - Prob. 11ECh. 14 - Prob. 12ECh. 14 - Prob. 13ECh. 14 - How does a multiple-baseline design rule out...Ch. 14 - Suppose (hat a complex therapy procedure contains...Ch. 14 - Prob. 16ECh. 14 - Briefly explain why a clinical psychologist might...
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- 15. This problem extends Problem 20.6. Let X, Y be random variables with finite mean. Show that 00 (P(X ≤ x ≤ Y) - P(X ≤ x ≤ X))dx = E Y — E X.arrow_forward(b) Define a simple random variable. Provide an example.arrow_forward17. (a) Define the distribution of a random variable X. (b) Define the distribution function of a random variable X. (c) State the properties of a distribution function. (d) Explain the difference between the distribution and the distribution function of X.arrow_forward
- 16. (a) Show that IA(w) is a random variable if and only if A E Farrow_forward15. Let 2 {1, 2,..., 6} and Fo({1, 2, 3, 4), (3, 4, 5, 6}). (a) Is the function X (w) = 21(3, 4) (w)+711.2,5,6) (w) a random variable? Explain. (b) Provide a function from 2 to R that is not a random variable with respect to (N, F). (c) Write the distribution of X. (d) Write and plot the distribution function of X.arrow_forward20. Define the o-field R2. Explain its relation to the o-field R.arrow_forward
- 7. Show that An → A as n→∞ I{An} - → I{A} as n→ ∞.arrow_forward7. (a) Show that if A,, is an increasing sequence of measurable sets with limit A = Un An, then P(A) is an increasing sequence converging to P(A). (b) Repeat the same for a decreasing sequence. (c) Show that the following inequalities hold: P (lim inf An) lim inf P(A) ≤ lim sup P(A) ≤ P(lim sup A). (d) Using the above inequalities, show that if A, A, then P(A) + P(A).arrow_forward19. (a) Define the joint distribution and joint distribution function of a bivariate ran- dom variable. (b) Define its marginal distributions and marginal distribution functions. (c) Explain how to compute the marginal distribution functions from the joint distribution function.arrow_forward
- 18. Define a bivariate random variable. Provide an example.arrow_forward6. (a) Let (, F, P) be a probability space. Explain when a subset of ?? is measurable and why. (b) Define a probability measure. (c) Using the probability axioms, show that if AC B, then P(A) < P(B). (d) Show that P(AUB) + P(A) + P(B) in general. Write down and prove the formula for the probability of the union of two sets.arrow_forward21. Prove that: {(a, b), - sa≤barrow_forwardarrow_back_iosSEE MORE QUESTIONSarrow_forward_ios
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