EBK BUSINESS STATISTICS
EBK BUSINESS STATISTICS
7th Edition
ISBN: 8220102743984
Author: STEPHAN
Publisher: PEARSON
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Chapter 1, Problem 1.37CRP

Results of a 2013 Adobe Systems study on retail apps and buying habits reveals insights on perceptions and attitudes toward mobile shopping using retail apps and browsers, providing new direction for retailers to develop their digital publishing strategies. Increased consumer interest in using shopping applications means retailers must adapt to meet the rising expectations for specialized mobile shopping experiences. The results indicate that tablet users (55%) are almost twice as likely as smartphone users (28%) to use their device to purchase products and services. The findings also reveal that retail and catalog apps are rapidly catching up to mobile browsers as a viable shopping channel: Nearly half of all mobile shoppers are interested in using apps instead of a mobile browser (45% of tablet shoppers and 49% of smartphone shoppers). The research is based on an online survey with a sample of 1,003 18–54 year olds who currently own a smartphone and/or tablet; it includes consumers who use and do not use these devices to shop (adobe.ly/11gt8Rq).

  1. Describe the population of interest.
  2. Describe the sample that was collected.
  3. Describe a parameter of interest.
  4. Describe the statistic used to estimate the parameter in (c).

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iid 1. The CLT provides an approximate sampling distribution for the arithmetic average Ỹ of a random sample Y₁, . . ., Yn f(y). The parameters of the approximate sampling distribution depend on the mean and variance of the underlying random variables (i.e., the population mean and variance). The approximation can be written to emphasize this, using the expec- tation and variance of one of the random variables in the sample instead of the parameters μ, 02: YNEY, · (1 (EY,, varyi n For the following population distributions f, write the approximate distribution of the sample mean. (a) Exponential with rate ẞ: f(y) = ß exp{−ßy} 1 (b) Chi-square with degrees of freedom: f(y) = ( 4 ) 2 y = exp { — ½/ } г( (c) Poisson with rate λ: P(Y = y) = exp(-\} > y! y²
2. Let Y₁,……., Y be a random sample with common mean μ and common variance σ². Use the CLT to write an expression approximating the CDF P(Ỹ ≤ x) in terms of µ, σ² and n, and the standard normal CDF Fz(·).
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