Because not all airline passengers show up for their reserved seat, an airline sells 125 tickets for a flight that holds only 124 passengers. The probability that a passenger does not show up is 0.10, and the passengers behave independently. Round your answers to two decimal places (e.g. 98.76). (a) What is the probability that every passenger who shows up gets a seat? (b) What is the probability that the flight departs with empty seats? (c) What are the mean and (d) standard deviation of the number of passengers who show up?

1. Use the​ 68-95-99.7 Rule to approximate the probability rather than using technology to find the values more precisely. The daily closing price of a stock​ (in $) is well modeled by a Normal model with mean ​$158.14 and standard deviation ​$4.64. According to this​ model, what cutoff​ value(s) of price would separate the following​ percentage? ​

a) highest 0.15​%

​b) highest ​50%

​c) middle 95​%

​d) highest 2.5​%

2. In the last quarter of​ 2007, a group of 64 mutual funds had a mean return of 4.6​% with a standard deviation of 2.5​%. Consider the Normal model ​N(0.046​, 0.025​) for the returns of these mutual funds.

​a) What value represents the 40th percentile of these​ returns?

​b) What value represents the 99th​ percentile? ​

c)​ What's the​ IQR, or interquartile​ range, of the quarterly returns for this group of​ funds?

A gas station has a 7% chance of running out of gas. What is the probability the gas station will run out of gas one day in the next week? What is the probability the gas station will run out of gas at least two days in the next week? What is the expected number of times the gas station will run out of gas?

he data in the accompanying table represent the heights and weights of a random sample of professional baseball players. Complete parts ​(a) through ​(c) below. LOADING... Click the icon to view the data table. ​(a) Draw a scatter diagram of the​ data, treating height as the explanatory variable and weight as the response variable. Choose the correct graph below. A. 70 76 82 180 210 240 Height (inches) Weight (pounds) A scatter diagram has a horizontal axis labeled “Height (inches)” from less than 70 to 82 plus in increments of 6 and a vertical axis labeled “Weight (pounds)” from less than 180 to 240 plus in increments of 30. The following 9 approximate points are plotted, listed here from left to right: (69, 186); (71, 200); (72, 180); (74, 190); (75, 230); (76, 218); (77, 198); (78, 228); (82, 232). B. 70 76 82 180 210 240 Height (inches) Weight (pounds) A scatter diagram has a horizontal axis labeled “Height (inches)” from less than 70 to 82 plus in increments of 6 and a vertical axis labeled “Weight (pounds)” from less than 180 to 240 plus in increments of 30. The following 9 approximate points are plotted, listed here from left to right: (69, 186); (71, 198); (72, 228); (74, 232); (75, 180); (75, 200); (75, 228); (76, 230); (82, 190). C. 70 76 82 180 210 240 Height (inches) Weight (pounds) A scatter diagram has a horizontal axis labeled “Height (inches)” from less than 70 to 82 plus in increments of 6 and a vertical axis labeled “Weight (pounds)” from less than 180 to 240 plus in increments of 30. The following 9 approximate points are plotted, listed here from left to right: (69, 186); (71, 200); (72, 180); (74, 190); (75, 198); (75, 228); (75, 230); (76, 228); (82, 232). ​(b) Determine the​ least-squares regression line. Test whether there is a linear relation between height and weight at the alphaequals0.05 level of significance. Determine the​ least-squares regression line. Choose the correct answer below. A. ModifyingAbove y with caretequals4.160xnegative 101.7 B. ModifyingAbove y with caretequals8.160xnegative 101.7 C. ModifyingAbove y with caretequals4.160xnegative 103.7 D. ModifyingAbove y with caretequalsnegative 101.7xplus4.160 Test whether there is a linear relation between height and weight at the alphaequals0.05 level of significance. State the null and alternative hypotheses. Choose the correct answer below. A. Upper H 0​: beta 0equals0 Upper H 1​: beta 0not equals0 B. Upper H 0​: beta 1equals0 Upper H 1​: beta 1greater than0 C. Upper H 0​: beta 0equals0 Upper H 1​: beta 0greater than0 D. Upper H 0​: beta 1equals0 Upper H 1​: beta 1not equals0 Determine the​ P-value for this hypothesis test. ​P-valueequals nothing ​(Round to three decimal places as​ needed.) State the appropriate conclusion at the alphaequals0.05 level of significance. Choose the correct answer below. A. Reject Upper H 0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. B. Do not reject Upper H 0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. C. Do not reject Upper H 0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. D. Reject Upper H 0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. ​(c) Remove the values listed for Player 4 from the data table. Test whether there is a linear relation between height and weight. Do you think that Player 4 is​ influential? Determine the​ P-value for this hypothesis test. ​P-valueequals nothing ​(Round to three decimal places as​ needed.) State the appropriate conclusion at the alphaequals0.05 level of significance. Choose the correct answer below. A. Reject Upper H 0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. B. Reject Upper H 0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. C. Do not reject Upper H 0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. D. Do not reject Upper H 0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. Do you think that Player 4 is​ influential? No Yes Player Height​ (inches) Weight​ (pounds) Player 1 76 227 Player 2 75 197 Player 3 72 180 Player 4 82 231 Player 5 69 185 Player 6 74 190 Player 7 75 228 Player 8 71 200 Player 9 75 230

The length of time a 1999 Honda Civic lasts before needing major repairs is normally distributed with a mean of 7 years and a standard deviation of 1.7 years.

a. What is the probability that a randomly selected 1999 Honda Civic lasts between 5.5 and 9 years?

b. If Honda Motor Company, Ltd. informed you that your Honda Civic is at 70th percentile, what is your Honda Civic’s years without major repairs?

c. A family-owned two Honda Civics. One of them is 1999 and lasted 7.5 years without a major repair. Other one (2002) lasted 9.0 years, but the distribution of 2002 Honda Civic had higher mean (8.4) with a standard deviation of 1.9 years. Which Honda Civic did better relative to other Honda Civics from the same year? (hint: Need to compare z scores from different normal distributions (1999 and 2002).

The International Air Transport Association surveys business travelers to develop quality ratings for transatlantic gateway airports. The maximum possible rating is 10. Suppose a simple random sample of  business travelers is selected and each traveler is asked to provide a rating for the Miami International Airport. The ratings obtained from the sample of  business travelers follow.

Develop a  confidence interval estimate of the population mean rating for Miami. Round your answers to two decimal places.

The heights of a simple random sample of soccer players in a particular league are given below. Can you conclude at the 5% level of significance, that the average height of soccer players in the league sampled is over 182 cm? Assume that the heights of soccer players is normal.

Show all of your work, include all necessary steps, and be complete in your answer and explanation.

The Chi-squared test has been used earlier to test a hypothesis about a population variance. It is also a hypothesis testing procedure for when one or more variables in the research are categorical (nominal).

Chi-squared Goodness of Fit Test

Chi-squared Test for Independency

Question 1. Describe an example of a research question where a Chi-squared test has been used. Mention the two hypotheses of the problem and display a numerical demonstration of your example. In particular, interpret the test P value in the context of your research example.

Question 2. Describe why the Chi-squared tests of the types mentioned above are always right-tailed hypothesis testing problems.

Anyone help please.......

Listed below are systolic blood pressure measurements​ (in mm​ Hg) obtained from the same woman. Find the regression​ equation, letting the right arm blood pressure be the predictor​ (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05 .

Right arm: 100, 99, 92, 80, 79

Left arm: 176, 170, 143, 145, 144

a. The regression equation is?

b. Given that the systolic blood pressure in the right arm is 90mm​ Hg, the best predicted systolic blood pressure in the left arm is _ mm hg

On March 29th the number of confirmed cases of the Covid-19 per state was obtained from the internet. A random number generator was used to get the sample data on the sheet named Sample data

What is the lower boundary on the 95% confidence interval for the whole number average of confirmed Covid 19 cases in the country?

What is the upper boundary on the 95% confidence interval for the whole number average of confirmed Covid 19 cases in the country?

The actual number of mean confirmed covid-19 cases in the United States is 2580. Did your confidence interval capture the mean? Why or why not?

Sample Data

A certain manufactured product is supposed to contain 23% potassium by weight. A sample of 10 specimens of this product had an average percentage of 23.2 with a standard deviation of 0.2. If the mean percentage is found to differ from 23, the manufacturing process will be recalibrated.

a) State the appropriate null and alternate hypotheses.

b) Compute the P-value.

c) Should the process be recalibrated? Explain.

What price do farmers get for their watermelon crops? In the third week of July, a random sample of 43 farming regions gave a sample mean of x = $6.88 per 100 pounds of watermelon. Assume that σ is known to be $1.98 per 100 pounds.

(a) Find a 90% confidence interval for the population mean price (per 100 pounds) that farmers in this region get for their watermelon crop. What is the margin of error? (Round your answers to two decimal places.)

(b) Find the sample size necessary for a 90% confidence level with maximal error of estimate E = 0.37 for the mean price per 100 pounds of watermelon. (Round up to the nearest whole number.)
______________ farming regions

(c) A farm brings 15 tons of watermelon to market. Find a 90% confidence interval for the population mean cash value of this crop. What is the margin of error? Hint: 1 ton is 2000 pounds. (Round your answers to two decimal places.)

Q#29. Visual sequential memory and poor spellers. Holmes, Malone, and Redenbach (2008) found that good readers and good spellers correctly read M = 93.8 (SD = 2.9) words from a spelling list. On the other hand, average readers and poor spellers correctly read M = 84.4 (SD = 3.0) words from the same spelling list. Assuming these data are normally distributed,

(a) What percentage of participants correctly read at least 90 words in the good readers/good spellers group? (use 2 decimal places) HINT: Calculate the z-score first. Then draw and shade the relevant portion of the curve. Finally, look up the proportion in the z table.
%

(b) What percentage of participants correctly read at least 90 words in the average readers/poor spellers group? (use 2 decimal places) HINT: See the hint above. NOTE. Use 84.4 rather than 84.8
%

Question 2

Suppose a researcher is interested in the effectiveness in a new childhood exercise program implemented in a SRS of schools across a particular county. In order to test the hypothesis that the new program decreases BMI (Kg/m²), the researcher takes a SRS of children from schools where the program is employed and a SRS from schools that do not employ the program and compares the results. Assume the following table represents the SRSs of students and their BMIs.

A) Assuming that all the necessary conditions are met (normality, independence, etc.) carry out the appropriate statistical test to determine if the new exercise program is effective. Use an alpha level of 0.05. Do not assume equal variances.

B) Construct a 95% confidence interval about your estimate for the average difference in BMI between the groups.

Choos the most appropriate option