A pharmacist has recently started a new private pharmacy and wanted to estimate the average waiting time to get prescribed medication in his pharmacy. He randomly selected 40 patients for observation and recorded how many minutes each waits. The mean waiting time was 28 minutes. Assuming that the waiting time follow a normal distribution with the standard deviation of 4 minutes, estimate the mean waiting time among all patients using a 95% confidence interval. Interpret this interval.

The average age of CEOs is 56 years. Assume the variable is normally distributed, with a standard deviation of 4 years. Give numeric answers with 4 decimal places.

a) If one CEO is randomly selected, find the probability that he/she is older than 63. Blank 1

b) If one CEO is randomly selected, find the probability that his/her mean age is less than 57. Blank 2

c) If one CEO is randomly selected, find the probability that his/her age will be between 53 and 59. Blank 3

d) If 36 CEOs are randomly selected, find the probability that their mean age is between 53 and 59. Blank 4

e) Explain the reason the answers to c) and d) above are differen

For a data set obtained from a sample, n = 79 and x = 45.30 . It is known that o = 4.1.

a. What is the point estimate of u?

The point estimate is ????????.

b. Make a 90% confidence interval for u .

Round your answers to two decimal places.

(???????, ??????)

c. What is the margin of error of estimate for part b?

Round your answer to three decimal places.

E =???????

An agent for a real estate company in a large city would like to be able to predict the monthly rental cost for​ apartments, based on the size of the​ apartment, as defined by square footage. A sample of eight apartments in a neighborhood was​ selected, and the information gathered revealed the data shown below. For these​ data, the regression coefficients are b 0 = 219.3999 and b 1 =0.9884.

Monthly Rent($) Size(Square Feet)
900 800
1,550 1,250
825 950
1,600 1,150
1,950 1,900
925 650
1,700 1,250
1,250 1,100

A. Determine the coefficient of​ determination, r2​, and interpret its meaning.

B. Determine the standard error of the​ estimate, Syx​, and interpret its meaning.

C. How useful is this model for predicting the monthly​ rent?

D. What other variables might explain the variation in monthly​ rent?

In a simple random sample of 120 Kansas seniors you found the mean out-of-pocket health care expenses for 2008 to be $4, 897. Assume σ=2,125.
i) How many people would you have to sample to estimate the mean out-of-pocket health care expenses in 2008 for all Kansas seniors to within $200 with 99% confidence? (5 points)

ii) Calculate and interpret a 98% confidence interval for the mean out-of-pocket health care expenses in 2008 for all Kansas seniors. (5 points)
iii) What is the margin of error for the interval calculated in part ii? (2 points)

please use APA format.

1. A researcher compared the adjustment of adolescents who had been raised in homes that were either very structured or very unstructured. Thirty adolescents from each type of family completed an adjustment inventory. The results are reported in the table below. Write the results as you would for the results section and the discussion section of your paper. Be sure to use APA format.

Means on Four Adjustment Scales for
Adolescents from Structured versus Unstructured Homes

A tire manufacturer warranties its tires to last at least 20 comma 000 miles or​ "you get a new set of​ tires." In its​ experience, a set of these tires last on average 28 comma 000 miles with SD 5 comma 000 miles. Assume that the wear is normally distributed. The manufacturer profits ​$200 on each set​ sold, and replacing a set costs the manufacturer ​$400. Complete parts a through c.

​(a) What is the probability that a set of tires wears out before 20 comma 000 ​miles? The probability is nothing that a set of tires wears out before 20 comma 000 miles. ​(Round to four decimal places as​ needed.)

​(b) What is the probability that the manufacturer turns a profit on selling a set to one​ customer? The probability is nothing that the manufacturer turns a profit on selling a set to one customer. ​(Round to four decimal places as​ needed.)

​(c) If the manufacturer sells 500 sets of​ tires, what is the probability that it earns a profit after paying for any​ replacements? Assume that the purchases are made around the country and that the drivers experience independent amounts of wear. The probability is nothing that the manufacturer earns a profit after paying for any replacements on 500 sets of tires. ​(Round to four decimal places as​ needed.)

For each of the following functions, does a constant c > 0 exist such that the function is a joint probability density function?

If yes, what is c? If not, why not?

Part (a) gives 2 points, parts (b)–(d) give each one point.

(a) f(x, y) = ( cxye −x−2y if x ≥ 0 and y ≥ 0, 0 otherwise.

(b) f(x, y) = ( cxye −x−2y if x ≥ −1 and y ≥ 1, 0 otherwise.

(c) f(x, y) = ( e −cxy if x ≥ 0 and y ≥ 1, 0 otherwise.

(d) f(x, y) = ( 1 y e −cxy if x ≥ 0 and y ≥ 1, 0 otherwise.

In the carnival game Under-or-Over-Seven, a pair of fair dice is rolled once, and the resulting sum determines whether the player wins or loses his or her bet. For example, the player can bet $1 that the sum will be under 7—that is, 2, 3, 4, 5, or 6. For this bet, the player wins $1 if the result is under 7 and loses $1 if the outcome equals or is greater than 7. Similarly, the player can bet $1 that the sum will be over 7—that is, 8, 9, 10, 11, or 12. Here, the player wins $1 if the result is over 7 but loses $1 if the result is 7 or under. A third method of play is to bet $1 on the outcome 7. For this bet, the player wins $4 if the result of the roll is 7 and loses $1 otherwise.

(a) Construct the probability distribution representing the different outcomes that are possible for a $1 bet on being under 7.

(b) Construct the probability distribution representing the different outcomes that are possible for a $1 bet on being over 7.

(c) Construct the probability distribution representing the different outcomes that are possible for a $1 bet on 7.

(d) Show that the expected long-run profit (or loss) to the player is the same, no matter which method of play is used.

QUESTION 16

Analyse the data below related to days survival following surgery from either stomach or lung cancer. What is the result of the Kolmogorov–Smirnov test for the patients who survived stomach cancer?

QUESTION 17

Run an independent t-test on the data in Q16. A Levene’s test result of p = .006 was obtained. What can we infer from this number?

QUESTION 18

What is the correct result for the independent t-test you calculated in Q17?

QUESTION 19

Assume that for the research into stomach and lung cancer the significance value is set at p < .05 and an independent t-test yielded a significance value of p = .06. What should you do?

QUESTION 20

What is the effect size for the cancer survival data?

In a certain article, laser therapy was discussed as a useful alternative to drugs in pain management of chronically ill patients. To measure pain threshold, a machine was used that delivered low-voltage direct current to different parts of the body (wrist, neck, and back). The machine measured current in milliamperes (mA). The pretreatment experimental group in the study had an average threshold of pain (pain was first detectable) at μ = 3.02 mA with standard deviation σ = 1.29 mA. Assume that the distribution of threshold pain, measured in milliamperes, is symmetrical and more or less mound-shaped. (Round your answers to two decimal places.)

(a) Use the empirical rule to estimate a range of milliamperes centered about the mean in which about 68% of the experimental group will have a threshold of pain from                       mA to                         mA

Discuss the concept of conditional probability and in what situations it would best be used. Do your best to cite examples from your own experiences at work or home.

A manufacturing company regularly conducts quality control checks at specified periods on the products it manufactures.​ Historically, the failure rate for LED light bulbs that the company manufactures is 18​%. Suppose a random sample of 10 LED light bulbs is selected. Complete parts​ (a) through​ (d) below. a. What is the probability that none of the LED light bulbs are​ defective? The probability that none of the LED light bulbs are defective is . 1374. ​(Type an integer or a decimal. Round to four decimal places as​ needed.) b. What is the probability that exactly one of the LED light bulbs is​ defective? The probability that exactly one of the LED light bulbs is defective is . 3017. ​(Type an integer or a decimal. Round to four decimal places as​ needed.) c. What is the probability that four or fewer of the LED light bulbs are​ defective? The probability that four or fewer of the LED light bulbs are defective is nothing. ​(Type an integer or a decimal. Round to four decimal places as​ needed.) d. What is the probability that five or more of the LED light bulbs are​ defective? The probability that five or more of the LED light bulbs are defective is nothing. ​(Type an integer or a decimal. Round to four decimal places as​ needed.)

A middle school is implementing a healthier lunch (low carbs, high protein) program for a variety of reasons, one of which is to decrease office referrals due to behavior. The new menu is used for an entire school year (9 months). The number of office referrals for each month from the previous year is compare to the months of the current year. Has the new menu significantly decreased office referrals? The t-test of related samples was conducted at the .05 level. The Statcrunch results are as follows. (11.5 points)

Paired T statistics

Hypothesis test results:
μ_D : mean of the paired difference between post and pre
H₀ : μ_D = 0
H_A : μ_D < 0

Step 1: Develop Hypotheses:

a.     Independent Variable =                                                   Scale: Categorical       Quantitative (1 pt)

b.    Dependent Variable =                                                     Scale: Categorical       Quantitative   (1 pt)

c.     Circle:     One-tailed       Two-tailed (1 pt)

d.    Alternative hypothesis in sentence form. (1 pt)                                                                                                                                                                                                                                                                                                                                                                                   

e.     Null hypothesis in sentence form. (1 pt)                                                                                                                                       

f.     Write the alternative and null hypotheses using correct notation. (1 pt)

                                                  H₁:                                                                H₀:                                                                                                                    

Step 2: Establish significance criteria (.05 pt)

g.     a =

Step 3: Calculate test statistic, effect size, confidence interval, and power (3 pts)

h.    t_calculated =                                                        Level of significance (p) =                                  

i.     Decision:      reject null or                   fail to reject null

j.     Calculate effect size =                                                                                             

Step 4: Draw conclusion (2 pts)

k.    Write your conclusion in sentence form including appropriate results notation.