Suppose the force acting on a column that helps to support a building is a normally distributed random variable \( X \) with a mean value of 17.0 kips and a standard deviation of 1.50 kips. Compute the following probabilities by standardizing and then using a standard normal curve table from the Appendix Tables or SALT. (Round your answers to four decimal places.)**(a)** \( P(X \leq 17) \)[Enter your answer]**(b)** \( P(X \leq 18.5) \)[Enter your answer]**(c)** \( P(X \geq 9.5) \)[Enter your answer]**(d)** \( P(15 \leq X \leq 20) \)[Enter your answer]**(e)** \( P(|X - 17| \leq 1) \)[Enter your answer]

As per our guidelines we are suppose to answer three sub parts .Mean()=17Standard deviation()=1.50

Answered: Suppose the force acting on a column…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Please do the following questions with full handwritten working out. Mean= 0.177911 Variance=0.057632
Suppose that average male weight in the US is 175 pounds with a standarddeviation of 25 pounds. Suppose you randomly select 1,000 male Americans and ask their weight, and average the 1,000 numbers to compute a sample mean Xn. A. What is the variance of the sample mean Xn? B. Use your answer to part (A), and Chebyshev’s inequality, to come up with a quantitative upper bound for the probability that sample mean Xn is more than a certain distance of 175
a.4/15 b.2/10 c.3/10 d.1/15 e.1/10
Please solve (a) & (b) only! Thanks.
The third worksheet labeled sample B is a simple random sample with replacement, with seven observations in the sample, from some population. The index i in the first column is just an integer name for each observation. The specific values x in the second column are measures of a random variable X distributed in the population. Now suppose this random variable X is known to have a Normal distribution in the sampled population. You still do not know the population mean and must estimate it from the sample, as you did earlier. BUT NOW, in this question, you know in advance that the true population standard deviation of the random variable X is 4. Compute the standard error (of the sample mean), given this new knowledge situation. i xi 1 74.2 2 72.79 3 70.35 4 74.37 5 73.34 6 78.96 7 77.99
Suppose in a local Kindergarten through 12th grade (K -12) school district, 49% of the population favor a charter school for grades K through 5. A simple random sample of 144 is surveyed. a. Find the mean and the standard deviation of X of B(144, 0.49). Round off to 4 decimal places. O = b. Now approximate X of B(144, 0.49) using the normal approximation with the random variable Y and the table. Round off to 4 decimal places. Y - N( c. Find the probability that at most 81 favor a charter school using the normal approximation and the table. (Round off to z-values up to 2 decimal places.) P(X 75) - P(Y > a (Z > e. Find the probability that exactly 81 favor a charter school using the normal approximation and the table. (Round off to z-values up to 2 decimal places.) P(X = 81) - P(
The third worksheet labeled sample B is a simple random sample with replacement, with seven observations in the sample, from some population. The index i in the first column is just an integer name for each observation. The specific values x in the second column are measures of a random variable X distributed in the population. Now suppose this random variable X is known to have a Normal distribution in the sampled population, BUT you do not know the population mean or the population standard deviation of that Normal distribution: Both must be estimated from the sample as you just did. Compute the lower bound of an 80% confidence interval for the population mean, using the appropriate sample estimates and techniques appropriate to the knowledge situation described above. i xi 1 74.2 2 72.79 3 70.35 4 74.37 5 73.34 6 78.96 7 77.99
A random sample of size n = 28 is obtained from a normally distributed population with a population mean of u = 350 and a variance of o =145. a. What is the probability that xr < 345? b. What is the probability that the sample variance is less than 140? c. What is the probability that the sample variance is greater than 175?
Suppose in a local Kindergarten through 12th grade (K -12) school district, 49% of the population favor a charter school for grades K through 5. A simple random sample of 144 is surveyed. a. Find the mean and the standard deviation of X of B(144, 0.49). Round off to 4 decimal places. O = b. Now approximate X of B(144, 0.49) using the normal approximation with the random variable Y and the table. Round off to 4 decimal places. Y - N( c. Find the probability that at most 81 favor a charter school using the normal approximation and the table. (Round off to z-values up to 2 decimal places.) P(X 75) - P(Y > a (Z > e. Find the probability that exactly 81 favor a charter school using the normal approximation and the table. (Round off to z-values up to 2 decimal places.) P(X = 81) - P(
A random sample of size n1 =15 is selected from a normal population with a mean of 76 and standard deviation of 9. A second random sample size n2 =10 is taken from another normal population with mean 71 and a standard deviation 13. Let x barı and x bar2 be the sample means. Find: a. The probability that xbar1 – xbar2 exceeds 4.5 b. The probability that 3.5 s xbar1– xbar2 s 5.5
Suppose the force acting on a column that helps to support a building is a normally distributed random variable X with mean value 12.0 kips and standard deviation 1.25 kips. Compute the following probabilities by standardizing and then using a standard normal curve table from the Appendix Tables. (Round your answers to four decimal places.) (a) P(X S 12) (b) P(X < 13.25) (c) P(X 2 5.75) (d) P(10 sxS 15) (e) P(IX – 12| s 2)
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