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The amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? O A. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. O B. The variable "weekly time spent watching television" is likely uniform, not normally distributed. OC. The variable "weekly time spent watching television" is likely skewed right, not normally distributed. O D. The variable "weekly time spent watching television" is likely normally distributed. O E. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. (b) According to a certain survey, adults spend 2.25 hours per day watching television on a weekday. Assume that the standard deviation for "time spent watching television on a weekday" is 1.93 hours. If a random sample of 40 adults is obtained, describe the sampling distribution of x, the mean amount of time spent watching television on a weekday. V with H =and o; = 3D (Round to six decimal places as needed.) (c) Determine the probability that a random sample of 40 adults results in a mean time watching television on a weekday of between 2 and 3 hours. The probability is . (Round to four decimal places as needed.)

The amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? O A. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. O B. The variable "weekly time spent watching television" is likely uniform, not normally distributed. OC. The variable "weekly time spent watching television" is likely skewed right, not normally distributed. O D. The variable "weekly time spent watching television" is likely normally distributed. O E. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. (b) According to a certain survey, adults spend 2.25 hours per day watching television on a weekday. Assume that the standard deviation for "time spent watching television on a weekday" is 1.93 hours. If a random sample of 40 adults is obtained, describe the sampling distribution of x, the mean amount of time spent watching television on a weekday. V with H =and o; = 3D (Round to six decimal places as needed.) (c) Determine the probability that a random sample of 40 adults results in a mean time watching television on a weekday of between 2 and 3 hours. The probability is . (Round to four decimal places as needed.)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The text discusses the distribution and likelihood of time spent by adults watching television, and how it impacts advertising on TV. It presents a series of statistical problems and asks users to engage with sampling distribution concepts. ### (a) Distribution Consideration The question asks about the expected distribution of the variable "weekly time spent watching television." Options are: - A: Likely symmetric, not normally distributed. - B: Likely uniform, not normally distributed. - **C (Selected): Likely skewed right, not normally distributed.** - D: Likely normally distributed. - E: Likely skewed left, not normally distributed. ### (b) Sampling Distribution Adults reportedly spend 2.25 hours/day watching TV on weekdays. The standard deviation for this is 1.93 hours. The question involves describing the sampling distribution (\( \bar{x} \)) for a sample of 40 adults. Formulas are provided for calculating the mean (\( \mu_{\bar{x}} = \)) and standard deviation (\( \sigma_{\bar{x}} = \)) of the sample mean, with a prompt to round to six decimal places. ### (c) Probability Calculation It queries the probability that a sample of 40 results in a mean TV watching time between 2 and 3 hours. Users must calculate and provide this probability, rounded to four decimal places. ### (d) Internet Use Effect The problem highlights that internet usage might reduce TV watching. A sample of 35 "avid internet users" watches TV for 1.81 hours/day. The task is to determine the probability of getting a sample mean of 1.81 hours or less from a population with a mean of 2.25 hours. Three options are given for interpreting this probability: - A: Expect 1 in 1000 samples. - B: Expect 40 in 1000 samples. - C: Expect 999 in 1000 samples. A checkbox question follows: "Based on the result obtained, do you think avid Internet users watch less television?" with "Yes" and "No" options. This layout is designed to guide students through understanding statistical distributions, sampling distributions, and related probabilities.
Transcribed Image Text:The text discusses the distribution and likelihood of time spent by adults watching television, and how it impacts advertising on TV. It presents a series of statistical problems and asks users to engage with sampling distribution concepts. ### (a) Distribution Consideration The question asks about the expected distribution of the variable "weekly time spent watching television." Options are: - A: Likely symmetric, not normally distributed. - B: Likely uniform, not normally distributed. - **C (Selected): Likely skewed right, not normally distributed.** - D: Likely normally distributed. - E: Likely skewed left, not normally distributed. ### (b) Sampling Distribution Adults reportedly spend 2.25 hours/day watching TV on weekdays. The standard deviation for this is 1.93 hours. The question involves describing the sampling distribution (\( \bar{x} \)) for a sample of 40 adults. Formulas are provided for calculating the mean (\( \mu_{\bar{x}} = \)) and standard deviation (\( \sigma_{\bar{x}} = \)) of the sample mean, with a prompt to round to six decimal places. ### (c) Probability Calculation It queries the probability that a sample of 40 results in a mean TV watching time between 2 and 3 hours. Users must calculate and provide this probability, rounded to four decimal places. ### (d) Internet Use Effect The problem highlights that internet usage might reduce TV watching. A sample of 35 "avid internet users" watches TV for 1.81 hours/day. The task is to determine the probability of getting a sample mean of 1.81 hours or less from a population with a mean of 2.25 hours. Three options are given for interpreting this probability: - A: Expect 1 in 1000 samples. - B: Expect 40 in 1000 samples. - C: Expect 999 in 1000 samples. A checkbox question follows: "Based on the result obtained, do you think avid Internet users watch less television?" with "Yes" and "No" options. This layout is designed to guide students through understanding statistical distributions, sampling distributions, and related probabilities.
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