I know that the sum of square of normal random variables follow a chi-square distribution. But when I learn how to do a goodness-fit test I don't know why the ratio of (O-E)^2/E follows a chi-square. I tried to square root of it first so that I might get something looks like a normal, but my new question arises : why (O-E)/sqrt(E) follows a normal-distribution?
I know from sampling distribution that if the sample is from the same distribution as the population then the sampling distribution of sample mean is approximately normal if n is large according to CLT, are those two concept related in some way?
Really struggle with this, appreciate for any comments and answer!!
I know that the sum of square of normal random variables follow a chi-square distribution. But...
When we carry out a chi-square goodness-of-fit test for a normal distribution, the null hypothesis states that the population: a) does not have a normal distribution. b) has a normal distribution. c) has a chi-square distribution. d) does not have a chi-square distribution. e) has k − 3 degrees of freedom.
In performing a chi-square goodness-of-fit test for a normal distribution, a researcher wants to make sure that all of the expected cell frequencies are at least five. The sample is divided into 7 intervals. The second through the sixth intervals all have expected cell frequencies of at least five. The first and the last intervals have expected cell frequencies of 1.5 each. After adjusting the number of intervals, the degrees of freedom for the chi-square statistic is O 2 3...
In performing a chi-square goodness-of-fit test for a normal distribution, a researcher wants to make sure that all of the expected cell frequencies are at least five. The sample is divided into 7 intervals. The second through the sixth intervals all have expected cell frequencies of at least five. The first and the last intervals have expected cell frequencies of 1.5 each. After adjusting the number of intervals, the degrees of freedom for the chi-square statistic is ____. 2, 3,5,...
3. Let X be normal random variable and Y be a Chi-square random variable with df degrees of freedom then the ratio follows (note that this is the reason we use a common test when We don't know for certain the true value of the variance): a) A x?distribution b) A normal distribution c) An F distribution d) At distribution.
Practice problems using various statistical methods If n independent random variables X have normal distributions with means μ and the standard deviations σ , then determine the distribution of a. I. X-E(X) var(X) C. 2. If n independent random variables Xi have normal distributions with means μί and the standard deviations σί, then determine the distribution of a. b. Y -a1X1 + a2X2+ + anXn (ai constant) X-E(X) Vvar(X) 3. What is CLT? Proof briefly? What are t-, Chi-squared- and...
a) true b) false 42. For a chi-square distributed random variable with 10 degrees of freedom and a level of sigpificanoe computed value of the test statistics is 16.857. This will lead us to reject the null hypothesis. a) true b) false 43. A chi-square goodness-of-fit test is always conducted as: a. a lower-tail test b. an upper-tail test d. either a lower tail or upper tail test e. a two-tail test 44. A left-tailed area in the chi-square distribution...
LU 22 2. We know that the sample variance follows a chi-square distribution: Sanx?(n-1). (a) (5 points) Use this fact to show that E(S) = 02. (Hint: Find the mean of the x as then mean of a Gamma distribution.) (b) (5 points) Use Markov's inequality to find an upper bound on the probability that the sample variance is twice the true variance, i.e. P(S? > 20%).
Prove that if random variable X follows a standard normal distribution (with mean u= 0 and standard deviation o = 1), then Y = X2 follows a chi-square distribution with 1 degree of freedom. In particular, show that My(t) = Mx2(t) = E[etX?), which equals the moment generating function of a chi-square distribution with 1 degree of freedom.
proof for distribution of (n-1)S^2/sigma^2 is the chi square distribution with n-1 degrees of freedom. I don't understand the expansion of the square, specifically how certain terms disappeared and how a sqrt(n) appeared. Also towards the end, why does V have a degree of freedom of 1? x A detailed explanation of what happened from step 2 to step 3 would be very helpful! THEOREM B The distribution of (n − 1)S2/02 is the chi-square distribution with n – 1...
A distribution and the observed frequencies of the values of a variable from a simple random sample of the population are provided below. Use the chi-square goodness-of-fit test to decide, at the specified significance level, whether the distribution of the variable differs from the given distribution Distribution: 0.1875, 0.1875, Observed frequencies: 16, 20, 24, 36 Significance level 0.05 0.3125, 0.3125 Determine the null and alternative hypotheses. Choose the correct answer below. OA. H: The distribution of the variable differs from...