24. For arandom sample of size n from a population of size N, consider the followingas an estimate of :where the ci are fixed numbers and Xi, , X, is the sample.a. Find a condition on the ci such that the estimate is unbiased.b. Show that the choice of c, that minimizes the variances of the estimate subjectto this condition is c1/n, wherei

Given for a random sample of size n the estimate of mean is given below.It is given that the…

Answered: 24. For arandom sample of size n from a…

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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21 - The average weekly income of 50 students randomly selected from a class is 250 TL with a variance of 16, a weekly average working time of 15 hours and a variance of 16. The average weight of the students was 60 kg and the variance was 9, and the average of their height was 160 cm and the variance was 25. Based on this information, which of the following is true of the variable with the greatest variation between observations? a) Income variable B) Income and working time variable NS) Height variable D) Working time variable TO) Weight variable
The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x<-rock$shape. Assume that the n area measurements x=(x1, x2,...,xn) are a random sample from a population with true unknown mean ? and true unknown variance ?2. Remember, let x be defined by x<-rock$shape.
With unit variance; the random variable Y is related to the random variable X by a linear relationship. A. Calculate the minimum error power when X and Y are fully correlated. B. Calculate the minimum error power when X and Y are not related at all.
The following data represent a random sample of 5 observations. Assume that Y is a linear function of X and a normally distributed disturbance term with a mean of zero and a constant variance. In other words: Y = a + bX + u, u ~ Observation Y X 1. 1 17 2. 3 13 3. 5 8 4. 7 10 5. 9 2 Create a scatterplot of this dataset (either manually, or by using Excel graphing functions) Calculate the sample means, variances, and standard deviations of the variables X and Y either “by hand” or by using Excel and write one sentence describing what each of these mean in terms of the dataset. The calculations below should be done by applying the bivariate regression formulas. In other words, do them “by hand” using a calculator or in Excel in a manner that I can clearly see the formulas you have used. You should also check your calculations by entering the data into an Excel sheet and using the regression analysis function under Data Tools.…
Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 46 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that ? = 7.50 ml/kg for the distribution of blood plasma. d)Find the sample size necessary for a 99% confidence level with maximal margin of error E = 2.60 for the mean plasma volume in male firefighters. (Round up to the nearest whole number.) =__ male firefighters What price do farmers get for their watermelon crops? In the third week of July, a random sample of 45 farming regions gave a sample mean of x = $6.88 per 100 pounds of watermelon. Assume that ? is known to be $2.00 per 100 pounds. (a) Find a 90% confidence interval for the population mean price (per 100 pounds) that…
3. Let X Pois(4). Find the distribution of Y = √X.
The built-in data set, rock, is a data frame recording the measurements of rock sample from a petroleum reservoir. We are interested in the area column of rock. Using R we can convert this column into the vector x by the assignment x30 we can create a confidence interval for μ using a normal critical value. If we want the confidence interval to be at the 94% level and we use a normal critical value, then what critical value should we use? i) Calculate a 94% confidence interval(using a normal critical value) for μ.
Let x₁ represent the sample mean cost (in thousands) to remodel a kitchen and x₂ represent the sample mean cost (in thousands) to remodel a master bedroom. A point estimate for the difference in these remodeling costs is desired, so x₁ - x₂ is needed. A sample mean is calculated as follows where x, is the sum of the given values and n is the sample size. X = n The sample of costs to remodel a kitchen, in thousands of dollars, are given. Kitchen 27.2 18.4 23.8 22.9 20.7 24.0 21.7 17.9
Let G and H be two independent unbiased estimators of 0. Assume that the variance of G is two times the variance of H. Find the constants a andb so that aG + bH is an unbiased estimator with the smallest possible variance for such a linear combination.
Psi is a measure of compressive strength, or the ability of the material to carry loads and handle compression. The desired concrete psi rating used for sidewalks and residential driveways ranges from 2500psi to 3000psi obtained from mixing cement, stone, and sand in different ratios but with the same amount of water. The summary of the psi's of three (3) such concrete mixes made by three (3) different civil engineering students is given as follows: Mean vector: The variance-covariance matrix: Concrete mix Mean Concrete mix 1 Concrete mix 2 Concrete mix 3 Concrete mix 1 | Concrete mix 2 2700 18 12 2 3000 12 16 3 2400 Concrete mix 3 16 25 Let the random variable Y be the vector of the psi's of concrete mixes obtained by the students, i.e. Y1, denotes the psi of concrete mix made by student 1, Y2 is the psi of concrete mix made by student 2 and Y3 is the psi of concrete mix psi made by student 3. (a) Find (i) the multivariate probability distribution function (pdf) of Y. (ii) the…
A manufacturing company produces bearings. One line of bearings is specified to be 1.64 centimeters (cm) in diameter. A major customer requires that the variance of the bearings be no more than .001 cm². The producer is required to test the bearings before they are shipped, and so the diameters of 16 bearings are measured with a precise instrument, resulting in the following values. Assume bearing diameters are normally distributed. Use the data and a = 0.01 to test to determine whether the population of these bearings is to be rejected because of too high a variance. 1.68 1.62 1.63 1.70 1.66 1.63 1.65 1.71 1.64 1.69 1.57 1.64 1.59 1.66 1.63 1.65 Appendix A Statistical Tables (Round your answer to 2 decimal places, e.g. 15.25.) The value of the test statistic is and we reject the null hypothesis ⇒
Let the X-values represent the times, in minutes, of preparation for a Statistics test; let the Y-values represent the points earned on the test. Assume that the sample of paired (X, Y) data is a simple random sample of quantitative data and the data have a bivariate normal distribution. Also, the scatterplot shows that the points approximate a straight-line pattern. If the sample has 35 pairs of values with (Zx,Zy,) = 11.41, and if we use a significance level of 0.05, calculate r and determine whether if there is sufficient evidence to support a claim of a linear correlation between X and Y.

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