For each of the following experiments describe the sample space.

A) Three dice are rolled.

B) 5 cards are dealt from a deck.

C) Temperature in front of a building is measured.

D) A student's overall academic performance is assessed.

The accompanying data represent the total travel tax​ (in dollars) for a​ 3-day business trip in 8 randomly selected cities. A normal probability plot suggests the data could come from a population that is normally distributed. A boxplot indicates there are no outliers. Complete parts​ (a) through​ (c) below. 67.62 78.42 70.61 84.97 80.32 85.33 100.83 99.72

​(a) Determine a point estimate for the population mean travel tax.

​(b) Construct and interpret a

9595​%

confidence interval for the mean tax paid for a​ three-day business trip.

(c) What would you recommend to a researcher who wants to increase the precision of the​ interval, but does not have access to additional​ data?

The Airline Passenger Association studied the relationship between the number of passengers on a particular flight and the cost of the flight. It seems logical that more passengers on the flight will result in more weight and more luggage, which in turn will result in higher fuel costs. For a sample of 20 flights, the correlation between the number of passengers and total fuel cost was 0.688.

1. State the decision rule for 0.025 significance level: H₀: ρ ≤ 0; H₁: ρ > 0. (Round your answer to 3 decimal places.)

2. Compute the value of the test statistic. (Round your answer to 2 decimal places.)

We have a class of 10 students who all spent different amounts of time studying for a quiz. The number of minutes each student studied is listed in the table below. Calculate the standard deviation of the class study time. Remember this is a population, not a sample. Round your answer to the nearest whole minute.

1. The standard deviation of study time for the class is equal to ____ minutes

Part 2:

The height of men in this class is normally distributed with a mean of 71 inches and a standard deviation of 2 inches.

A) A man who has a height of 60 inches is which of the following: A. Shorter than average B. Taller than average C. Above average

B) Because the data are normally distributed we know that approximately ____% of the men in this class have heights between 69 and 73 inches.

C) A man with a height of 75 inches is ____ standard deviations above the mean.

D) The z-score for a man who is 78 inches is ______

In a clinic, a random sample of 60 patients is obtained, and each person’s red blood cell
count (in cells per microliter) is measured. The sample mean is 5.28. The population
standard deviation for red blood cell counts is 0.54.

(a) At the 0.01 level of significance, test the claim that the sample is from a population

with a mean less than 5.4. [4 marks]
(b) What is the Type 11 error ,6 in the hypothesis testing of Part (a) if the true mean of
the population is 5.17? [7 marks]

(0) The Type 11 error fl in Part (b) is considered to be too large and it is decided to
reduce fl to 0.1. With the same sample size, find the new Type I error a. [7 marks]

Can someone please explain these problems, I don't understand, please and thank you!!

The patients in the Digoxin trial dataset can be considered a population of people suffering from heart failure. These patients were examined before the drug trial began, and their heart rate and blood pressure were recorded. The mean and standard deviation of the variables are listed below. Each variable follows a normal distribution.

Heart rate (beats/min)                          μ = 78.8            σ = 12.66

Systolic blood pressure (mmHg)             μ = 125.8          σ = 19.94

1. A patient with a heart rate of 90 is

1. in the middle 68% of values
2. in the middle 95% of values (but not the middle 68%)
3. in the 5% most extreme values

2. The 10% of patients with the highest heart rates have z scores greater than 1.28 What heart rate does this value correspond to? Report your answer to 2 decimal places.

3. Many random samples of 25 patients are selected from this population, and the mean of their systolic blood pressures is calculated. The many sample means make up a sampling distribution. What is the mean of the sampling distribution (its center)? In other words, what is the mean of the many sample means? Report your answer to 2 decimal places.

4. If μ is the mean from the previous question, 68% of the sample means have values between

1. μ – 0.798 and μ + 0.798
2. μ – 3.988 and μ + 3.988
3. μ – 7.976 and μ + 7.976
4. μ – 19.94 and μ + 19.94

5. The 10% of samples with the highest mean systolic blood pressure have z scores greater than 1.282. What mean blood pressure does this correspond to?

Please only show me the graphs I know the answers to below problems. I don't know how to do the graphs correctly.

1. A radar unit is used to measure speeds of cars on a motorway. The speeds are normally distributed with a mean of 90 km/hr and a standard deviation of 10 km/hr. What is the probability that a car picked at random is travelling at more than 100 km/hr?

2. For a certain type of computers, the length of time bewteen charges of the battery is normally distributed with a mean of 50 hours and a standard deviation of 15 hours. John owns one of these computers and wants to know the probability that the length of time will be between 50 and 70 hours.

3. Entry to a certain University is determined by a national test. The scores on this test are normally distributed with a mean of 500 and a standard deviation of 100. Tom wants to be admitted to this university and he knows that he must score better than at least 70% of the students who took the test. Tom takes the test and scores 585. Will he be admitted to this university?

How does anti smoking messages inpack the population off today

A global research study found that the majority of​ today's working women would prefer a better​ work-life balance to an increased salary. One of the most important contributors to​work-life balance identified by the survey was​ "flexibility," with 45​% of women saying that having a flexible work schedule is either very important or extremely important to their career success. Suppose you select a sample of 400 working women.

The probability that in the sample fewer than 53​% say that having a flexible work schedule is either very important or extremely important to their career success is

The probability that in the sample between 41​% and 53​% say that having a flexible work schedule is either very important or extremely important to their career success is

The probability that in the sample more than 47​% say that having a flexible work schedule is either very important or extremely important to their career success is

A quality expert inspects 420 items to test whether the population proportion of defectives exceeds .03, using a right-tailed test at α = .02.

(a) What is the power of this test if the true proportion of defectives is ππ = .05? (Round your intermediate calculations and final answer to 4 decimal places.)

Power:

(b) What is the power of this test if the true proportion is ππ = .06? (Round your intermediate calculations and final answer to 4 decimal places.)

Power:

(c) What is the power of this test if the true proportion of defectives is ππ = .07? (Round your intermediate calculations and final answer to 4 decimal places.)

Power:   

You are manager of a ticket agency that sells concert tickets. You assume that people will call 4 times in an attempt to buy tickets and then give up. Each telephone ticket agent is available to receive a call with probability 0.25. If all agents are busy when someone calls, the caller hears a busy signal.

Find n, the minimum number of agents that you have to hire to meet your goal of serving 95% of the customers calling to buy tickets.

Quantitative Methods II

This assignment relates to the following Course Learning Requirements:

[CLR 1] Calculate the chance that some specific event will occur at some future time • knowledge of the normal probability distribution

[CLR 2] Perform Sampling Distribution and Estimation

[CLR 3] Conduct Hypothesis Testing

[CLR 4] Understand and calculate Regression and Correlation

Objective of this Assignment:    To conduct a regression and correlation analysis

Instructions:

The term paper involves conducting a regression and correlation analysis on any topic of your choosing. The paper must be based on yearly data for any economic or business variable, for a period of at least 20 years

(Note: the source of the data must be given. Data which is not properly documented as to source is unacceptable and paper will be graded F. Textbook examples are unacceptable).

The paper can be between 3 to 5 pages (1500 to 2000 words).

The term paper should distinguish between dependent and independent variables; determine the regression equation by the least squares method; plot the regression line on a scatter diagram; interpret the meaning of regression coefficients; use the regression equation to predict values of the dependent variable for selected values of the independent variable and construct forecast intervals and calculate the standard error of estimate, coefficients of determination (r2) and correlation (r) and interpret the meaning of the coefficients (r2) and (r). Your regression and correlation analysis must:

1. Graph the data (scatter diagram)

2. Use the method of least squares to derive a trend equation and trend values

3. Use check column to verify computations ∑ (Y-Yc)=0

4. Superimpose trend equation on scatter diagram.

5. Use your model to predict the movement of the variable for the next year.

6. Compare your predictions with the actual behavior of the variable during the 21styear .

Transplant operations have become routine. One common transplant operation is for kidneys. The most dangerous aspect of the procedure is the possibility that the body may reject the new organ. There are several new drugs available for such circumstances and the earlier the drug is administered, the higher the probability of averting rejection. The New England Journal of Medicine recently reported the development of a new urine test to detect early warning signs that the body is rejecting a transplanted kidney. However, like most other tests, the new test is not perfect. In fact, 20% of negative tests and 9% of positive tests prove to be incorrect. Physicians know that in about 32% of kidney transplants the body tries to reject the organ. If the new test has a positive result (indicating early warning of rejection), what is the probability that the body is attempting to reject the kidney?

The Donner Party: Natural Selection in Action The Donner Party is the name of emigrants who travelled in covered wagons from Illinois to California in 1846 and became trapped in the Sierra Nevada Mountains when the region was hit by heavy snows in late October. By the time the survivors were rescued in April, 1847, 40 out of 87 had died from famine and exposure to severe cold. Some of those that survived did so by resorting to cannibalism, according to newspapers reporting at that time. Data on the survivorship of the party members may be used to gain some insight into human behavior and natural selection under extreme stress. For example, some questions of interest are whether males are better able to withstand harsh conditions than females and the extent to which the chances of survival vary with age. The data in the lab assignment come from Grayson, (1990), “Donner Party Deaths: A Demographic Assessment,” Journal of Anthropological Research, v.46. The data are also available in the StatCrunch file lab3.txt located on the STAT 151 Laboratories web site at http://www.stat.ualberta.ca/statslabs/stat151/index.htm (click Stat 151 link, and Data for Lab 3). The data are not to be printed in your submission. The following is a description of the variables in the data file: Variable Name Description of Variable NAME full name of the passenger, GENDER gender (female or male); FAMILY family name, POSITION member status within the family, AGE estimated age (in years) as of July 31, 1846; CHILD child (yes or no) SURVIVAL survived or died, ORDER order of death, ALONE Yes if travelling alone (no family, no close accompanying persons), GROUP SIZE Number of group members. 1. Is it an observational study or a randomized experiment? Can the data be generalized to a broader population? If females in the study turned out to be more apt to survive than males, could this be used as proof that, in general, females are better able than males to withstand harsh conditions? 4. In this question, you will examine the relationship between survival and gender. (a) Were the chances of survival different for females than for males? In order to answer the question, obtain the contingency table of survival by gender. Make sure that Row percent, Column percent, and Percent of Total as well as Chi-Square test for independence are selected. Paste the table into your report. (b) Using α = 0.05, test that there was no relationship between survival and gender. State the null and alternative hypotheses. Report the value of the appropriate test statistic, the distribution of the test statistic under the null hypothesis, and the P-value of the test to answer the question. State your conclusion. (c) Refer to the output in part (a) to answer the following questions: What percent of the survivors were females? What percent were female survivors? (d) Using α = 0.05, is there evidence that there was a difference in the survival rate for females and males? Carry out the appropriate two-sample proportion test. State the null and alternative hypotheses. Report the value of the appropriate test statistic, the distribution of the test statistic under the null hypothesis, and the P-value of the test to answer the question. State your conclusion. (e) What is the relationship between the tests in parts (b) and (d)? 3 (f) Obtain and interpret a 95% confidence interval for the difference in survival rates of females and males?