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A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. 16 Refer to Exhibit 7-4. The standard error of the mean equals 0.3636 0.0331 0.0200 4.0000

A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. 16 Refer to Exhibit 7-4. The standard error of the mean equals 0.3636 0.0331 0.0200 4.0000

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Exhibit 7-4 A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. 16 Refer to Exhibit 7-4. The standard error of the mean equals a 0.3636 0.0331 0.0200 d 4.0000 17 The t distribution is a family of similar probability distributions, with each individual distribution depending on a parameter known as the a finite correction factor b sample size degrees of freedom standard deviation d 18 As the sample size increases, the margin of error a increases b decreases stays the same d None of the answers is correct. 19 If we want to provide a 95% confidence interval for the mean of a population, the confidence coefficient is a 0.485 b 1.96 0.95 d 1.645 Exhibit 8-1 In order to estimate the average time spent on the computer terminals per student at a local university, data were collected from a sample of 81 business students over a one-week period. Assume the population standard deviation is 1.2 hours 20 Refer to Exhibit 8-1. The standard error of the mean is a 7.5 b 0.014 0.16 d 0.133 21 Refer to Exhibit 8-1. If the sample mean is 9 hours, then the 95% confidence interval is approximately 7.04 to 110.96 hours a b 7.36 to 10.64 hours 7.80 to 10.20 hours d 8.74 to 9.26 hơurs 22 Whenever the population standard deviation is unknown, which distribution is used in developing an interval estimate for a population mean? a standard distribution b z distribution binomial distribution d t distribution 23 We can use the normal distribution to make confidence interval estimates for the population proportion, p, when np 2 5 n(1 -p)25 a b p has a normal distribution d np 2 5 and n (1 -p)25 24 The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called the standard error b a residual a prediction interval d the variance 25 Regression analysis is a statistical procedure for developing a mathematical equation that describes how one independent and one or more dependent variables are related several independent and several dependent variables are related one dependent and one or more independent variables are related a b ld None of the answers is correct. 26 A least squares regression line may be used to predict a value of y if the corresponding x value is given a b implies a cause-effect relationship between x and y can only be determined if a good linear relationship exists between x and y d All of the answers are correct. 27 In simple linear regression, r is the estimated regression equation b coefficient of correlation sum of the squared residuals d coefficient of determination 28 If a data set has SST = 2,000 and SSE = 800, then the coefficient of determination is a 0.4 b 0.6 0.5 d 0.8 29 A data point (observation) that does not fit the trend shown by the remaining data is called а (n) a residual b outlier point estimate d None of the answers is correct. Exhibit 14-3: Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained. ỹ= 12+ 1.8x n= 17 SSR = 225 SSE = 75 30 Refer to Exhibit 14-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is a $66,000 b $5,412 $66 d $17,400
Transcribed Image Text:Exhibit 7-4 A random sample of 121 bottles of cologne showed an average content of 4 ounces. It is known that the standard deviation of the contents (i.e., of the population) is 0.22 ounces. 16 Refer to Exhibit 7-4. The standard error of the mean equals a 0.3636 0.0331 0.0200 d 4.0000 17 The t distribution is a family of similar probability distributions, with each individual distribution depending on a parameter known as the a finite correction factor b sample size degrees of freedom standard deviation d 18 As the sample size increases, the margin of error a increases b decreases stays the same d None of the answers is correct. 19 If we want to provide a 95% confidence interval for the mean of a population, the confidence coefficient is a 0.485 b 1.96 0.95 d 1.645 Exhibit 8-1 In order to estimate the average time spent on the computer terminals per student at a local university, data were collected from a sample of 81 business students over a one-week period. Assume the population standard deviation is 1.2 hours 20 Refer to Exhibit 8-1. The standard error of the mean is a 7.5 b 0.014 0.16 d 0.133 21 Refer to Exhibit 8-1. If the sample mean is 9 hours, then the 95% confidence interval is approximately 7.04 to 110.96 hours a b 7.36 to 10.64 hours 7.80 to 10.20 hours d 8.74 to 9.26 hơurs 22 Whenever the population standard deviation is unknown, which distribution is used in developing an interval estimate for a population mean? a standard distribution b z distribution binomial distribution d t distribution 23 We can use the normal distribution to make confidence interval estimates for the population proportion, p, when np 2 5 n(1 -p)25 a b p has a normal distribution d np 2 5 and n (1 -p)25 24 The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called the standard error b a residual a prediction interval d the variance 25 Regression analysis is a statistical procedure for developing a mathematical equation that describes how one independent and one or more dependent variables are related several independent and several dependent variables are related one dependent and one or more independent variables are related a b ld None of the answers is correct. 26 A least squares regression line may be used to predict a value of y if the corresponding x value is given a b implies a cause-effect relationship between x and y can only be determined if a good linear relationship exists between x and y d All of the answers are correct. 27 In simple linear regression, r is the estimated regression equation b coefficient of correlation sum of the squared residuals d coefficient of determination 28 If a data set has SST = 2,000 and SSE = 800, then the coefficient of determination is a 0.4 b 0.6 0.5 d 0.8 29 A data point (observation) that does not fit the trend shown by the remaining data is called а (n) a residual b outlier point estimate d None of the answers is correct. Exhibit 14-3: Regression analysis was applied between sales data (in $1000s) and advertising data (in $100s), and the following information was obtained. ỹ= 12+ 1.8x n= 17 SSR = 225 SSE = 75 30 Refer to Exhibit 14-3. Based on the above estimated regression equation, if advertising is $3,000, then the point estimate for sales (in dollars) is a $66,000 b $5,412 $66 d $17,400
1 A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is a b (а- b) (b - a) d 1/(b - a) 2 The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability of assembling the product between 7 and 9 minutes is a b 0.5 0.2 1 3 Larger values of the standard deviation result in a normal curve that is shifted to the right a b shifted to the left narrower and more peaked wider and flatter d 4 For the standard normal probability distribution, the area to the left of the mean is a -0.5 b 0.5 any value between 0 and 1 d 1 5 Assume z is a standard normal random variable. Then P(1.41<z <2.85) equals la 0.4772 b 0.3413 0.8285 d None of the answers is correct. 6 Suppose x is a normally distributed random variable with a mean of 8 and a standard deviation of 4. The probability that x is between 1.48 and 15.56 is a 0.0222 b 0.419 0.5222 0.919 Exhibit 6-5: The weight of items pr oduced by a machine is nor mally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. 7 Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh more than 10 ounces? a 0.3413 b 0.8413 0.1587 d 0.5 8 A continuous probability distribution that is useful in describing the time, or space, between occurrences of an event is a(n)_ probability distribution. la normal b uniform exponential d Poisson 9 The basis for using a normal probability distribution to approximate the sampling distribution of i and 5 is Chebyshev's theorem the empirical rule a b the central limit theorem d Bayes' theorem if it involves an ongoing process 10 The population being studied is usually considered that makes listing or counting every element in the population impossible. la finite b infinite skewed d symmetric 11 A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size N has the same probability of being selected n has a probability of .5 of being selected n has a probability of.1 of being selected n has the same probability of being selected a b d 12 A single numerical value used as an estimate of a population parameter is known as a parameter population parameter parameter or a population parameter point estimate b d 13 The standard deviation of all pos sible Tvalues is called the standard error of proportion b standard error of the mean mean deviation central variation d 14 As the sample size increases, the standard deviation of the population decreases population mean increases a b standard error of the mean decreases standard error of the mean increases Exhibit 7-2 Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said "yes," and 100 said "no." 15 Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond "yes" is a 300 b approximately 300 0.75 d 2.5
Transcribed Image Text:1 A continuous random variable is uniformly distributed between a and b. The probability density function between a and b is a b (а- b) (b - a) d 1/(b - a) 2 The assembly time for a product is uniformly distributed between 6 and 10 minutes. The probability of assembling the product between 7 and 9 minutes is a b 0.5 0.2 1 3 Larger values of the standard deviation result in a normal curve that is shifted to the right a b shifted to the left narrower and more peaked wider and flatter d 4 For the standard normal probability distribution, the area to the left of the mean is a -0.5 b 0.5 any value between 0 and 1 d 1 5 Assume z is a standard normal random variable. Then P(1.41<z <2.85) equals la 0.4772 b 0.3413 0.8285 d None of the answers is correct. 6 Suppose x is a normally distributed random variable with a mean of 8 and a standard deviation of 4. The probability that x is between 1.48 and 15.56 is a 0.0222 b 0.419 0.5222 0.919 Exhibit 6-5: The weight of items pr oduced by a machine is nor mally distributed with a mean of 8 ounces and a standard deviation of 2 ounces. 7 Refer to Exhibit 6-5. What is the probability that a randomly selected item will weigh more than 10 ounces? a 0.3413 b 0.8413 0.1587 d 0.5 8 A continuous probability distribution that is useful in describing the time, or space, between occurrences of an event is a(n)_ probability distribution. la normal b uniform exponential d Poisson 9 The basis for using a normal probability distribution to approximate the sampling distribution of i and 5 is Chebyshev's theorem the empirical rule a b the central limit theorem d Bayes' theorem if it involves an ongoing process 10 The population being studied is usually considered that makes listing or counting every element in the population impossible. la finite b infinite skewed d symmetric 11 A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size N has the same probability of being selected n has a probability of .5 of being selected n has a probability of.1 of being selected n has the same probability of being selected a b d 12 A single numerical value used as an estimate of a population parameter is known as a parameter population parameter parameter or a population parameter point estimate b d 13 The standard deviation of all pos sible Tvalues is called the standard error of proportion b standard error of the mean mean deviation central variation d 14 As the sample size increases, the standard deviation of the population decreases population mean increases a b standard error of the mean decreases standard error of the mean increases Exhibit 7-2 Four hundred registered voters were randomly selected and asked whether gun laws should be changed. Three hundred said "yes," and 100 said "no." 15 Refer to Exhibit 7-2. The point estimate of the proportion in the population who will respond "yes" is a 300 b approximately 300 0.75 d 2.5
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