# statistics

Let X be the average of a sample of 16 independent normal random variables with mean 0 and variance 1. Determine c such that P (X< c) = .5

1. 👍 0
2. 👎 0
3. 👁 200

## Similar Questions

1. ### Probability

For each of the following statements, determine whether it is true (meaning, always true) or false (meaning, not always true). Here, we assume all random variables are discrete, and that all expectations are well-defined and

2. ### stats

A normal population has mean 100 and variance 25. How large must the random sample be if we want the standard error of the sample average to be 1.5? I know the answer is 12. Would someone please be able to explain! and share what

3. ### Probability

Let X and Y be two normal random variables, with means 0 and 3 , respectively, and variances 1 and 16 , respectively. Find the following, using the standard normal table. Express your answers to an accuracy of 3 decimal places. 1.

4. ### Math

1.)Suppose you interview 10 randomly selected workers and ask how many miles they commute to work. You'll compute the sample mean commute distance. Now imagine repeating the survey many, many times, each time recording a different

1. ### Probability

1.Let π and π be two binomial random variables: a.If π and π are independent, then π+π is also a binomial random variable b.If π and π have the same parameters, π and π , then π+π is a binomial

2. ### statistics

The Gamma distribution Gamma(πΌ,π½) with paramters πΌ>0 , and π½>0 is defined by the density ππΌ,π½(π₯)=π½πΌΞ(πΌ)π₯πΌβ1πβπ½π₯,for allπ₯β₯0. The Ξ function is defined by

3. ### Probability

Problem 1 Suppose that X, Y, and Z are independent, with E[X]=E[Y]=E[Z]=2, and E[X2]=E[Y2]=E[Z2]=5. Find cov(XY,XZ). cov(XY,XZ)= ? Problem 2. Let X be a standard normal random variable. Another random variable is determined as

4. ### science

what should you ask yourself when looking for an independent variable in an experiment? I would ask whether that variable can be manipulated or not. Here is more info on experimental variables that might be helpful. An independent

1. ### probability

Let π and π be independent continuous random variables that are uniformly distributed on (0,1) . Let π»=(π+2)π . Find the probability π(lnπ»β₯π§) where π§ is a given number that satisfies π^π§

2. ### probability

For each of the following sequences, determine the value to which it converges in probability. (a) Let X1,X2,β¦ be independent continuous random variables, each uniformly distributed between β1 and 1. Let

3. ### Probability

For each of the following sequences, determine the value to which it converges in probability. (a) Let X1,X2,β¦ be independent continuous random variables, each uniformly distributed between β1 and 1. Let

4. ### Probability

Let N,X1,Y1,X2,Y2,β¦ be independent random variables. The random variable N takes positive integer values and has mean a and variance r. The random variables Xi are independent and identically distributed with mean b and variance