A healthcare provider monitors the number of CAT scans performed each month in each of
its clinics. The most recent year of data for a particular clinics follows (the reported variable is the
number of CAT scans each month expressed as the number of CAT scans per thousand members of the
health plan):

2.31, 2.09, 2.36, 1.95, 1.98, 2.25, 2.16, 2.07, 1.88, 1.94, 1.97, 2.02.

Find a two-sided 95% confidence interval for the standard deviation.

A nutritionist is interested in the relationship between cholesterol and diet. The nutritionist developed a non-vegetarian and vegetarian diet to reduce cholesterol levels. The nutritionist then obtained a sample of clients for which half are told to eat the new non-vegetarian diet and the other half to eat the vegetarian diet for five months. The nutritionist hypothesizes that the non-vegetarian diet will increase cholesterol levels more. What can the nutritionist conclude with α = 0.05. Below are the cholesterol levels of all the participants after five months.

non- vegetarian	vegetarian
106 121 141 146 156 196 106 106	126 171 196 108 231 256 131 196

If appropriate, compute the CI. If not appropriate, input "na" for both spaces below.
[   ,   ]

e) Compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and/or select "na" below.
d =   ;  ---Select--- na trivial effect small effect medium effect large effect
r² =   ;  ---Select--- na trivial effect small effect medium effect large effect

In 2014, a group of students was interested in investigating prices of rental accommodation in suburbs of Brisbane that are close to the CBD and collected information on a total of 200 randomly chosen dwellings in four inner western suburbs. A subset of this data, relating to rental apartments in these suburbs is included below. The variables are:

Per week: weekly rental price for the apartment ($);

Bedrooms: number of bedrooms in the apartment;

Sqm: size of the apartment (m²)

Furnished: whether the apartment was furnished or not (yes/no).

The values are;

265,2,59,No

305,2,70,No

300,1,72,No

320,3,66,No

340,2,113,Yes

330,2,58,Yes

355,2,63,No

345,2,57,Yes

355,2,61,No

360,2,114,Yes

355,2,75,Yes

360,2,68,No

365,2,64,No

370,1,69,No

390,2,73,Yes

380,2,85,Yes

390,2,56,Yes

370,2,56,Yes

385,2,59,Yes

380,2,65,Yes

385,2,62,Yes

400,2,65,No

415,2,69,Yes

400,3,63,No

405,3,70,No

420,2,77,No

435,2,84,Yes

435,2,83,Yes

455,2,73,Yes

450,2,72,Yes

485,2,68,No

500,2,76,Yes

535,2,97,No

290,1,60,No

305,1,63,Yes

330,2,65,No

310,2,70,No

335,2,64,No

330,2,62,No

345,2,79,No

355,1,81,No

340,2,66,No

345,1,60,No

345,2,64,No

355,2,73,No

385,2,61,No

380,2,78,No

405,2,81,No

410,2,76,Yes

430,2,80,No

440,2,61,No

450,3,86,No

485,3,91,No

500,1,87,No

545,1,97,Yes

345,3,86,No

400,2,72,No

400,2,74,No

480,2,73,Yes

755,3,87,No

760,3,77,No

770,3,113,No

824,2,109,No

860,3,104,No

295,1,70,No

290,1,54,No

295,1,61,No

325,1,61,No

340,2,56,No

355,2,61,No

365,2,95,No

420,1,75,No

420,2,66,No

440,2,74,No

480,3,72,No

465,3,87,No

470,1,87,Yes

490,1,81,Yes

495,2,76,No

505,2,97,No

530,2,77,No

545,2,97,No

560,2,79,No

550,2,78,No

560,3,75,No

565,1,96,Yes

580,2,85,Yes

605,3,84,No

605,2,93,Yes

610,2,78,Yes

620,2,87,No

665,2,88,No

700,2,80,No

750,3,97,Yes

740,3,124,No

805,3,101,No

860,3,98,No

960,3,123,Yes

990,3,102,Yes

1195,3,133,No

1190,3,137,No

1405,3,148,Yes

1490,3,154,No

Question 3)

The students were interested in the proportion of rental apartments in these suburbs that were leased as furnished apartments, and whether this varied with the number of bedrooms in these apartments. To investigate further whether the proportions of furnished apartments differ between apartments with different numbers of bedrooms, it is useful to test formally whether the number of bedrooms in an apartment and whether it is furnished or not are independent.

a) Test whether the number of bedrooms in an apartment and whether it is furnished or not is independent.

b) State the null hypothesis, the relevant form of the test statistic and the approximate distribution of the test statistic for carrying out this text.

c) Perform a hypothesis test with using α = 0.05, of whether the proportions of furnished apartments vary across number of bedrooms, that is, whether the furnishing status of an apartment is independent of the number of bedrooms in the apartment.

Include the Following:

i) The table of expected frequencies

ii) The observed value of the test statistic

iii) The relevant degrees of freedom for the distribution of the test statistic

IV) The resulting p-value for the test, or a rejection region

Conclude the test by interpreting the p-value (or rejection region and your observed test statistic) in terms of the original question discussed above

Pls do this question with R code !!!!

During the independent research 30 women were chosen to measure their weight. The
mean value of weight is 66 kg and it is known from the previous experience that the weight is normally
distributed with ? = 10 kg.

a) Find a 95% two-sided confidence interval on the mean weight.

b) Find a 90% two-sided confidence interval on the mean weight.

c) Which interval is wider?

Describe how to write the null and alternative hypotheses based on a claim. Provide at least one example to clarify your explanation.

(I need your Reference URL LINK, please)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please)

Q1. Define the following terms:
A. Contingency table (Introduction to Biostatistics)
B. Chi-square test (Introduction to Biostatistics)
Q2. List the assumptions required to perform a chi-square test? (Introduction to Biostatistics)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please)

Applying statistical analysis skills to real-world decision making is key in modern business and it can make a company to be ahead competitively. Even in today’s workplace, you can have an immediate competitive edge over other new employees, and even those with more experience, by applying statistical analysis skills. Chose any company that you have observed that it is not utilizing its data as your case study. Do some background research on the company? Write an essay (report) outlining some statistical data analysis that the company can use in its decision making. Relate how data analysis can be attained by using built-in R-programming packages or functions.

Prove that if two of the opposite sides of a quadrilateral are respectively the greatest and the least sides of the quadrilateral, then the angles adjacent to the least are greater than their opposite angles

2017-2018 Goals
49
44
43
42
42
41
40
40
39
39
39
37
36
36
35
35
34
34
34
34

2012-2013 Goals
32
29
28
26
23
23
23
22
22
21
21
21
20
20
20
19
19
18
18
18

2007-2008 Goals
65
52
50
47
43
43
42
41
40
40
38
38
36
36
35
34
34
33
33
32

Given the above three sets of data, we want to compare the three seasons using the ANOVA. Answer the following questions:

1. Using proper notation, write the null and alternative hypothesis statements.

2. In the context of the problem posed, interpret the results of the test and make a conclusion about the hypotheses.

****You must be provide concise explanations in your solutions in order to receive credit****

Here is a simple probability model for multiple-choice tests. Suppose that each student has probability p of correctly answering a question chosen at random from a universe of possible questions. (A strong student has a higher p than a weak student.) The correctness of answers to different questions are independent. Jodi is a good student for whom p = 0.8.

(a) Use the Normal approximation to find the probability that Jodi scores 74% or lower on a 100-question test. (Round your answer to four decimal places.)

(b) If the test contains 250 questions, what is the probability that Jodi will score 74% or lower? (Use the normal approximation. Round your answer to four decimal places.)

(c) How many questions must the test contain in order to reduce the standard deviation of Jodi's proportion of correct answers to half its value for a 100-item test?

Test the given claim. Identify the null​ hypothesis, alternative​ hypothesis, test​ statistic, P-value, and then state the conclusion about the null​ hypothesis, as well as the final conclusion that addresses the original claim. Among

20912091

passenger cars in a particular​ region,

227227

had only rear license plates. Among

344344

commercial​ trucks,

4848

had only rear license plates. A reasonable hypothesis is that commercial trucks owners violate laws requiring front license plates at a higher rate than owners of passenger cars. Use a

0.100.10

significance level to test that hypothesis.

a. Test the claim using a hypothesis test.

b. Test the claim by constructing an appropriate confidence interval.

7. A recent Iowa straw poll for the Democratic Primary found the following number of supporters for these candidates (Observed Frequencies).

Elizabeth Warren	Bernie Sanders	Joe Biden	Pete Buttigieg
20	25	10	25

a) Specify the null and alternative hypotheses for a chi-square Goodness of Fit test of candidate preference.

b) Fill in the table below with the expected frequencies.

Elizabeth Warren	Bernie Sanders	Joe Biden	Pete Buttigieg

c) Use the observed and expected frequencies to calculate a chi-square Goodness of Fit test to decide if people in Iowa have a preference for any of the candidates, using alpha = .05. Report the critical value and your decision.

A roulette wheel has 38 slots, numbered 0, 00, and 1 to 36. The slots 0 and 00 are colored green, 18 of the others are red, and 18 are black.The dealer spins the wheel and at the same time rolls a small ball along the wheel in the opposite direction. The wheel is carefully balanced so that the ball is equally likely to land in any slot when the wheel slows. Gamblers can bet on various combinations of numbers and colors. (a)If you bet on “red,” you win if the ball lands in a red slot. What is the probability of winning with a bet on red in a single play of roulette? (b)You decide to play roulette four times, each time betting on red. What is the distribution of X, the number of times you win? (c)If you bet the same amount on each play and win on exactly four of the eight plays, then you will “break even.” What is the probability that you will break even? (d)If you win on fewer than four of the eight plays, then you will lose money. What is the probability that you will lose money?

Given the following information, is the grade dependent on gender? Test at the 0.05 level. State the hypotheses and identify the claim, find the critical value(s), compute the test value, make the decision, summarize the results. A B C D or lower

Males 8 17 25 10

Females 12 10 21 7

Does the average Presbyterian donate more than the average Catholic in church on Sundays? The 44 randomly observed members of the Presbyterian church donated an average of $22 with a standard deviation of $12. The 58 randomly observed members of the Catholic church donated an average of $17 with a standard deviation of $10. What can be concluded at the αα = 0.10 level of significance?

1. For this study, we should use Select an answert-test for the difference between two independent population meansz-test for a population proportiont-test for the difference between two dependent population meansz-test for the difference between two population proportionst-test for a population mean
2. The null and alternative hypotheses would be:   
3.   

H0:H0:  Select an answerp1μ1 ?=<≠> Select an answerμ2p2 (please enter a decimal)   

H1:H1:  Select an answerp1μ1 ?=><≠ Select an answerμ2p2 (Please enter a decimal)

3. The test statistic ?tz = (please show your answer to 3 decimal places.)
4. The p-value = (Please show your answer to 4 decimal places.)
5. The p-value is ?≤> αα
6. Based on this, we should Select an answerfail to rejectrejectaccept the null hypothesis.
7. Thus, the final conclusion is that ...
   • The results are statistically insignificant at αα = 0.10, so there is statistically significant evidence to conclude that the population mean amount of money that Presbyterians donate is equal to the population mean amount of money that Catholics donate.
   • The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the mean donation for the 44 Presbyterians that were observed is more than the mean donation for the 58 Catholics that were observed.
   • The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the population mean amount of money that Presbyterians donate is more than the population mean amount of money that Catholics donate.
   • The results are statistically insignificant at αα = 0.10, so there is insufficient evidence to conclude that the population mean amount of money that Presbyterians donate is more than the population mean amount of money that Catholics donate.