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Reality TV and cosmetic surgery. Refer to the Body Image: An International Journal of Research (March 201 0) study of the impact of reality TV shows on a college student’s decision to undergo cosmetic surgery, Exercise 12.43 (p. 715). The data saved in the file were used to fit the interaction model, E(y) = β0 + β0x1 + β2x4 + β3x1x4, where y = desire to have cosmetic surgery (25-point scale), x1 = {1 if male, 0 if female}, and x4 = impression of reality TV (7-point scale). From the SPSS printout (p. 715), the est1mated equation is:
- a. Give an estimate of the change in desire (y) for every 1-point increase in impression of reality TV show (x4) for female students.
- b. Repeat part a for male students.
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Chapter 12 Solutions
Statistics for Business and Economics (13th Edition)
- A well-known company predominantly makes flat pack furniture for students. Variability with the automated machinery means the wood components are cut with a standard deviation in length of 0.45 mm. After they are cut the components are measured. If their length is more than 1.2 mm from the required length, the components are rejected. a) Calculate the percentage of components that get rejected. b) In a manufacturing run of 1000 units, how many are expected to be rejected? c) The company wishes to install more accurate equipment in order to reduce the rejection rate by one-half, using the same ±1.2mm rejection criterion. Calculate the maximum acceptable standard deviation of the new process.arrow_forward5. Let X and Y be independent random variables and let the superscripts denote symmetrization (recall Sect. 3.6). Show that (X + Y) X+ys.arrow_forward8. Suppose that the moments of the random variable X are constant, that is, suppose that EX" =c for all n ≥ 1, for some constant c. Find the distribution of X.arrow_forward
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- 3. Let X1, X2,..., X, be independent, Exp(1)-distributed random variables, and set V₁₁ = max Xk and W₁ = X₁+x+x+ Isk≤narrow_forward7. Consider the function (t)=(1+|t|)e, ER. (a) Prove that is a characteristic function. (b) Prove that the corresponding distribution is absolutely continuous. (c) Prove, departing from itself, that the distribution has finite mean and variance. (d) Prove, without computation, that the mean equals 0. (e) Compute the density.arrow_forward1. Show, by using characteristic, or moment generating functions, that if fx(x) = ½ex, -∞0 < x < ∞, then XY₁ - Y2, where Y₁ and Y2 are independent, exponentially distributed random variables.arrow_forward
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