Aplia, 1 term Printed Access Card for Gravetter/Wallnau's Essentials of Statistics for the Behavioral Sciences, 8th
8th Edition
ISBN: 9781285079707
Author: Frederick J Gravetter, Larry B. Wallnau
Publisher: Cengage Learning
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Chapter 14.6, Problem 2LC
To determine
The effect of increase of value of X by 1 point on Y through the equation
Y = − 3 X + 7
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Chapter 14 Solutions
Aplia, 1 term Printed Access Card for Gravetter/Wallnau's Essentials of Statistics for the Behavioral Sciences, 8th
Ch. 14.1 - For each of the following, indicate whether you...Ch. 14.1 - The data points would be clustered more closely...Ch. 14.1 - If the data points are clustered close to a line...Ch. 14.1 - If a scatter plot shows a set of data points that...Ch. 14.2 - Can SP ever have a value less than zero?Ch. 14.2 - Calculate the sum of products of deviations (SP)...Ch. 14.2 - Prob. 3LCCh. 14.3 - A researcher finds a correlation of r = 0.71...Ch. 14.3 - A researcher finds a correlation of r = 0.60...Ch. 14.4 - A researcher obtains a correlation of r = 0.39 for...
Ch. 14.4 - As sample size gets smaller, what happens to the...Ch. 14.4 - Sales figures show a positive relationship between...Ch. 14.5 - Describe what is measured by a Spearman...Ch. 14.5 - Prob. 2LCCh. 14.5 - Prob. 3LCCh. 14.5 - The following data represent job-related stress...Ch. 14.5 - Prob. 2LCACh. 14.6 - A local gym charges a 25 monthly membership fee...Ch. 14.6 - Prob. 2LCCh. 14.6 - Prob. 3LCCh. 14.6 - If the slope constant (b) in a linear equation is...Ch. 14.6 - Prob. 1LCACh. 14.6 - Prob. 1LCBCh. 14.6 - Prob. 2LCBCh. 14.6 - Prob. 3LCBCh. 14.6 - Prob. 1LCCCh. 14 - a. What information is provided by the sign (+ or...Ch. 14 - Calculate SP (the sum of products of deviations)...Ch. 14 - Calculate SP (the sum of products of deviations)...Ch. 14 - For the following scores, X Y 1 3 3 5 2 1 2 3 a....Ch. 14 - For the following scores, X Y 1 7 4 2 1 3 1 6 2 0...Ch. 14 - Prob. 6PCh. 14 - With a small sample, a single point can have a...Ch. 14 - For the following set of scores, X Y 6 4 3 1 5 0 6...Ch. 14 - Judge and Cable (2010) report the results of a...Ch. 14 - The researchers cited in the previous problem also...Ch. 14 - Identifying individuals with a high risk of...Ch. 14 - As we have noted in previous chapters, even a very...Ch. 14 - A researcher measures three variables, X, Y, and...Ch. 14 - Prob. 17PCh. 14 - The regression equation is intended to be the best...Ch. 14 - A set of n = 20 pairs of scores (X and Y values)...Ch. 14 - A set of n = 25 pairs of scores (X and Y values)...Ch. 14 - For the following set of data, a. Find the linear...Ch. 14 - Does the regression equation from Problem 20...Ch. 14 - Prob. 23PCh. 14 - Although you might suspect that dissatisfied...Ch. 14 - Problem 9 examined the relationship between weight...Ch. 14 - There appears to be some evidence suggesting that...Ch. 14 - The regression equation is computed for a set of n...Ch. 14 - a. One set of 20 pairs of scores, X and Y values,...Ch. 14 - a. A researcher computes the regression equation...
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- 11. Prove or disprove: (a) If is a characteristic function, then so is ²; (b) If is a non-negative characteristic function, then so is √√4.arrow_forward4. Suppose that P(X = 1) = P(X = -1) = 1/2, that Y = U(-1, 1) and that X and Y are independent. (a) Show, by direct computation, that X + Y = U(-2, 2). (b) Translate the result to a statement about characteristic functions. (c) Which well-known trigonometric formula did you discover?arrow_forward9. The concentration function of a random variable X is defined as Qx(h) = sup P(x ≤ X ≤x+h), h>0. x (a) Show that Qx+b (h) = Qx(h). (b) Is it true that Qx(ah) =aQx(h)? (c) Show that, if X and Y are independent random variables, then Qx+y (h) min{Qx(h). Qy (h)). To put the concept in perspective, if X1, X2, X, are independent, identically distributed random variables, and S₁ = Z=1Xk, then there exists an absolute constant, A, such that A Qs, (h) ≤ √n Some references: [79, 80, 162, 222], and [204], Sect. 1.5.arrow_forward
- 29 Suppose that a mound-shaped data set has a must mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 6 and 12? b. About what percentage of the data should lie between 4 and 6? c. About what percentage of the data should lie below 4? 91002 175/1 3arrow_forward2,3, ample and rical t? the 28 Suppose that a mound-shaped data set has a mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 8 and 12? b. About what percentage of the data should lie above 10? c. About what percentage of the data should lie above 12?arrow_forward27 Suppose that you have a data set of 1, 2, 2, 3, 3, 3, 4, 4, 5, and you assume that this sample represents a population. The mean is 3 and g the standard deviation is 1.225.10 a. Explain why you can apply the empirical rule to this data set. b. Where would "most of the values" in the population fall, based on this data set?arrow_forward
- 30 Explain how you can use the empirical rule to find out whether a data set is mound- shaped, using only the values of the data themselves (no histogram available).arrow_forward5. Let X be a positive random variable with finite variance, and let A = (0, 1). Prove that P(X AEX) 2 (1-A)² (EX)² EX2arrow_forward6. Let, for p = (0, 1), and xe R. X be a random variable defined as follows: P(X=-x) = P(X = x)=p. P(X=0)= 1-2p. Show that there is equality in Chebyshev's inequality for X. This means that Chebyshev's inequality, in spite of being rather crude, cannot be improved without additional assumptions.arrow_forward
- 4. Prove that, for any random variable X, the minimum of EIX-al is attained for a = med (X).arrow_forward8. Recall, from Sect. 2.16.4, the likelihood ratio statistic, Ln, which was defined as a product of independent, identically distributed random variables with mean 1 (under the so-called null hypothesis), and the, sometimes more convenient, log-likelihood, log L, which was a sum of independent, identically distributed random variables, which, however, do not have mean log 1 = 0. (a) Verify that the last claim is correct, by proving the more general statement, namely that, if Y is a non-negative random variable with finite mean, then E(log Y) log(EY). (b) Prove that, in fact, there is strict inequality: E(log Y) < log(EY), unless Y is degenerate. (c) Review the proof of Jensen's inequality, Theorem 5.1. Generalize with a glimpse on (b).arrow_forward3. Prove that, for any random variable X, the minimum of E(X - a)² is attained for a = EX. Provedarrow_forward
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