Please answer parts d e and f. The answers to the rest have been
answered repeatedly here and no one completes the problem. Thank
you.
d) Observe that
Therefore,
Hence qr is a strictly decreasing function of r for r > 0.
e) Observe that if pr is maximized at r, then,
Hence, the result follows.
f) The following table gives us the value of qr at r:
r | q |
2 | 0.0828968254 |
3 | 0.0328968254 |
4 | -0.0004365079365 |
5 | -0.02543650794 |
6 | -0.04543650794 |
7 | -0.0621031746 |
8 | -0.07638888889 |
9 | -0.08888888889 |
10 | -0.1 |
Hence the maximum for pr occurs at r = 3 and the value of the maximum is 0.398
Please answer parts d e and f. The answers to the rest have been answered repeatedly...
Probability and Conditional Independence Suppose there are two types of candidates good candidates G and bad candidates Gº. There are two interviews that a candidate can be selected for: 11 and 12, (I denotes the candidate not getting the first intreview, 15 denotes the candidate not getting the second interview). Here below we list the conditional probabilities for good and bad candidates respectively: Consider the conditional probability table below: Probability Value PIIN 12G) 0.0625 Plin 12G) 0.1875 P(I Ո IS|G)...
can anyone check my answers? thx!
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Please
code in java
There are N employees already working for a company and M new candidates eligible for the work. At the end of the financial year, each of the N employees demand for an increment. You are provided with the data of current_salary and the salary he/she expects. Also, there are M candidates we can recruit. We have the data of salary demanded by each eligible candidate. The company can spend maximum of X units of money. Now...
Code using R or Python PLEASE ANSWER e-h the rest have been answered. We observe from our campus the temperature and count the number of squirrels. Our observations are T = [52, 52, 50, 54, 50, 52, 54, 80, 80] Sq = [8, 10, 6, 9, 6, 12, 12, 1, 0] a) What is the covariance of these vectors? (1point) -39.1358 b) What is the covariance matrix? (1point) 15.254 -4.348 -4348 1.863 c) What is the correlation coefficient? (1point) -.8158...
1. An application in probability (a) A function p(q) is a probability measure if p(x) > 0VT E R and (r) dx = 1. We first show that p(x):= vino exp(-) is a probability measure. (1) Compute dr. (ii) Show that were dr = 1. (ii) (1pt) Conclude that pr(I) is a probability measure. (b) A random variable x(): R + R is an integrable function that assigns a numerical value, X(I), to the outcome of an experiment, I, with...
Please answer the question (d), (e), (f).
11. (12 points, 2 points each) Find the computational complexity for the following code fragments: (a Nyhoff p. 364 Drozdek pp. 72-73, f Weiss, p. 72) a. for (int x = 1, count = 0, 1-0; i < n; i++) for (int j 0; j <= x; j++) counttti x = 2; b. for (int count 0, i = 0; i < n; i++) for (int j = 0; j < n; j++)...
(b)
(c) and (d) please
Problem(5) (a) (1 pt) Let Z~ Normal(0, 1). Recall the definition of z-value, i.e., P(Z > zr) = r. Find the probability of P(-70/2 < 3 < 2a/2). (b) (4 points) Let X1, X2, ... , Xn be a random sample from some population with (un- known) mean u and (known) variance o?. Based on the Central Limit Theorem and part (a) above, show that the confidence intervals for the population mean y can be...
5. Doing (much) Better by Taking the Min Let X be a random variable that takes on the values in the set {1,...,n} that satisfies the inequality Pr( x i) Sali for some value a>0 and all i € {1,...,n}. Recall that (or convince yourself that) E(X) = P(X= i) = Pr(x2i). 1. Given what little you know so far, give the best upper bound you can on E(X). 2. Let X1 and X2 be two independent copies of X...
I only need help with d, e, and f. Can you
please explain especially d in detail? Thank
you
1. Here you will prove the famous identity that 1 1 1 3+5+7+ Do not use the Ratio Test anywhere in this question. (a) Express h as a power series centered at 0. Determine its interval of convergence. Hint: This should be short. (b) Let S(:) be the Taylor series of arctan x at 0. Without computing S(2), briefly explain why...
PLEASE ANSWER ALL parts .
IF YOU CANT ANSWER ALL, KINDLY ANSWER PART (E) AND
PART(F)
FOR PART (E) THE REGRESSION MODEL IS ALSO GIVE AT THE
END.
REGRESSION MODEL:
We will be returning to the mtcars dataset, last seen in assignment 4. The dataset mtcars is built into R. It was extracted from the 1974 Motor Trend US magazine, and comcaprises fuel consumption and 10 aspects of automobile design and performance for 32 automobiles (1973-74 models). You can find...