3. Sir Harold Jeffreys, doesn’t like the way Fisher teaches statistics and decides to teach a class on ‘Bayesian Statistics’. Toward the end of the quarter, he also asks his students to form teams of 1 to 4 individuals to work on a group project. Let \( Y \) be the team size for a specific group project in Jeffreys’ class. The following table shows the cdf of \( Y \):\[\begin{array}{|c|c|c|c|c|}\hliney & 1 & 2 & 3 & 4 \\\hlineP(Y \leq y) & 0.12 & 0.38 & 0.75 & 1 \\\hline\end{array}\](a) What is the probability that a team has two students in Jeffreys’ class?(b) Compute the probability that a team in Jeffreys’ class has at least 2 students. Compared to Fisher’s from question 2, which class has a higher probability of having teams of at least two students?(c) Compute the expected team size in Jeffreys’ class. Is it greater than the expected team size in Fisher’s class?(d) Suppose that in the table of the cdf of \( Y \) the value of \( P(Y \leq 3) \) was missing, that is, suppose you saw the following table:\[\begin{array}{|c|c|c|c|c|}\hliney & 1 & 2 & 3 & 4 \\\hlineP(Y \leq y) & 0.12 & 0.38 & ? & 1 \\\hline\end{array}\]Would it be possible to retrieve \( P(Y \leq 3) \) by using the information available in the table? If yes, show how to do it, if not, briefly explain why.

(a) The probability that 2 students were in the class is calculated as:…

Answered: 3. Sir Harold Jeffreys, doesn't like…

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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#25). Both photos are the same problem.
A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…
THIS IS ENGINEERING DATA ANALYSIS 1. Given the following: c = 5, x1 = 7, x2 = 8, x3 = 10, x4 = 11, x5 =13, y1 = 5, y2 = 7, y3 = 9, y4 = 11, y5 = 13.Evaluate the following:
Consider the following difference-in-differences estimator for the effect of a newgarbage incinerator on housing values. Rumor of a new incinerator being built in a townin Massachusetts began after 1978, and construction began in 1981. You have data onprices of houses that sold in 1978, and another sample of those that sold in 1981. Youdefine a dummy variable (y81) as equal to 1 if the house sold in 1981, and zero if thehouse sold in 1978. Your hypothesis is that the price of houses located near theincinerator will fall across those years relative to the price of more distant houses. Youdefine a house as being near the incinerator (nearinc) if it is within 3 miles of it. Housingprice (price) is measured in real terms, in 1978 dollars. You estimate the followingregression (standard errors are in parentheses): price = 82,517.23 + 18,790.29y81 -18,824.37nearinc (2,726.91) (4,050.07) (4,875.32) -11,863.90(y81 * nearinc) (7,456.65) n=321 Interpret the coeffiecient…
3. Fill in the blank spaces of table B1 using information compiled in table B. Table B Breusch-Godfrey Serial Correlation LM Test: Prob. F(2,55) Prob. Chi-Square(2) F-statistic 11.70006 0.0001 Obs*R-squared 17.90823 0.0001 Table B1: Breusch-Godfrey Serial Correlation LM Test F-statistic: Probability: a. Write down the null and alternative hypotheses underlying Breusch-Godfrey serial correlation (autocorrelation) test. b. Will you accept or reject the null hypothesis based on the Breusch-Godfrey test for residual autocorrelation? Why or why not?
The following results were obtained in a study of correlation coefficient between two variables X and Y : n=50, x =10, o,=3; y O, = 2; r. = 0.3. xy || However, on subsequent verification it was found that one value of X = 10 and one value of Y = 6 were inaccurate and hence weedėd out. With the remaining values how is the original value of correlation coefficient affected.
#26). Both photos are the same problem.
5. Use the following table to answer the question given below. Coefficient of correlation Dimension Sig (p) with variable F A -0.053 0.000 B 0.821 0.000 C -0.755 0.000 D 0.255 0.000 E -0.632 0.000 7 Comment on the correlation coefficient values (i.e. the relationship and its strength) given in the above table.
5. (10) A recent Gallup Organization Poll asked male and female Americans whether they were pro or pro choice when it comes to abortion issues. The results of the survey are as follows: life Opinion Pro-Life Pro-Choice Gender Men 195 200 Women 240 250 Test whether an individual's opinion regarding abortion is independent of gender at the a = 0.025 level of significance.
In each of the following scenarios there is something wrong. Describe what is wrong and give a reason for you the answer. 1) If you multiply a random vriable by 10, then the mean is multiplied by 10 and the variance is multiplied by 10. 2) When finding then mean of the sum of two random variables, you need to know the correlation between them.
12. The following means, standard deviations and correlations are found for X1 = = seed hay crop in cwts. per acre, X2 = spring rainfall in inches, X3 = accumulated temperature above 42° F in spring, in a certain district of England during twenty years. %3D |3D X = 28-02, 01=4-42, r12 =+ 0-80, 0.40, X2 = 4.91, 02 = 1·10, r13 =- -- Ò -56. %3D X3 = 594, ơ3 = 85, r23 = - 0-56. %3D Find the partial correlations and the regression equations for hay-crop on spring rainfall and accumulated temperature,

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