A youth and money survey, sponsored by the american savings education council talked to 1,000 students about their personal finance, ages 16-22. The survey found that 33% of students in this age group have their own credit card. if a sub sample of 100 students is taken from this survey what is the probability that 40 or less will have their own credit card?

A.) Using the normal approximation for the binomial solve this problem, show all of your work in solving the problem.

A new production process is being contemplated for the manufacture of stainless steel bearings. Measurements of the diameters of random samples of bearings from the old and new processes produced the following data (all in mm): Old

.

A. Can you conclude that the variances between the new and old procedure are different? Use formal hypothesis testing.

b. Can you conclude that there is a difference in mean diameter between the procedures? Use formal hypothesis testing.

c. Management wants to know if the new procedure is comparable to the old procedure. What can you tell them? (Give a yes/no answer and your reasoning, based on statistics.)

In a certain​ country, the true probability of a baby being a

girl

is

0.461

Among the next

four

randomly selected births in the​ country, what is the probability that at least one of them is a

boy​?

The probability is.

You may need to use the appropriate technology to answer this question.

Are nursing salaries in City A lower than those in City B? As reported by a newspaper, salary data show staff nurses in City A earn less than staff nurses in City B. Suppose that in a follow-up study of 40 staff nurses in City A and 50 staff nurses in City B you obtain the following results. Assume population variances are unknown and unequal.

(a)

Formulate hypotheses so that, if the null hypothesis is rejected, we can conclude that salaries for staff nurses in City A are significantly lower than for those in City B. Use

α = 0.05.

H₀: μ₁ − μ₂ = 0

H_a: μ₁ − μ₂ < 0

H₀: μ₁ − μ₂ < 0

H_a: μ₁ − μ₂ ≠ 0

H₀: μ₁ − μ₂ ≤ 0

H_a: μ₁ − μ₂ > 0

H₀: μ₁ − μ₂ > 0

H_a: μ₁ − μ₂ = 0

H₀: μ₁ − μ₂ ≠ 0

H_a: μ₁ − μ₂ = 0

(b)

What is the value of the test statistic? (Round your answer to three decimal places.)

(c)

What is the p-value? The degrees of freedom for this test are 87. (Round your answer to four decimal places.)

p-value =

Compare the firstplace finish times for men and women. If the 53 men and women runners had competed as one group, in what place would winner of women's marathon have finished? Round your answer to 2 decimal places.

The first place runner in the men’s group finished  minutes _______aheadbehind of the first place runner in the women’s group.

b. What is the median time for men and women runners? Compare men and women runners based on their median times. Round your answers to 2 decimal places.

Using the median finish times, the men’s group finished  minutes _______aheadbehind of the women’s group.

c. Provide a five-number summary for both the men and the women. Round your answers to 2 decimal places.

d. Are there outliers in either group?

If data contain outliers enter the value. If there no outliers live answer blank. If there is more than one value, separate your answers with commas (to 2 decimals).

Outliers in the men's group.

Outliers in the women's group.

e. Which of the following box plots accurately displays the data set?

_________Box plot #1Box plot #2Box plot #3Box plot #4

Did men or women have the most variation in finish times?

_______MenWomen

please be very specific on showing work done!!

If Z∼N(μ=0,σ2=1)Z∼N(μ=0,σ2=1), find the following probabilities:

1. P(Z<1.58)=P(Z<1.58)=
2. P(Z=1.58)=P(Z=1.58)=
3. P(Z>−.27)=P(Z>−.27)=
4. P(−1.97<Z<2.46)=

Qualitative, Quantitative, Discrete, Continuous.

Required:

(a) List 5 qualitative variables and 5 quantitative variables seen around the home.

(b) List 5 discrete and 5 continuous variables found at home, at work, on TV or any other location.

In each case explain the reason(s) for your answers.  

1. 7 During the period of time that a local university takes phone-in registrations, calls come in at the rate of one every two minutes.
   1. What is the probability of receiving NO calls in a 10-minute period?
   2. What is the probability of receiving more than five calls in a 10-minute period?
   3. What is the probability of receiving less than seven calls in 15-minutes?
   4. What is the probability of receiving at least three but no more than 10 calls in 12 minutes?

USING EXCEL

A marketing firm wants to know how strongly Cuyahoga County residents support building a new stadium for the local national football league team, the Cleveland Browns. They get a complete list of all residents in Cuyahoga County, along with their addresses and phone numbers.   There are 52 zip codes in the county. From each of those zip codes, 10 Cuyahoga County residents are randomly selected and surveyed.

1. Describe the population.

2. What is the sample?

3. What type of sampling design was used? Explain.  

Show algebraically that E(Var(β1hat)) = σ^2/(n-1)σ_x²

QUESTION 6 Using Table A, p.690-691, the area to the right of the z score 0.52 would be a. 0.52 b. 0.6985 c. 0.3015 d. -0.52

QUESTION 7 The data point 91 is taken from a normal distribution that has a mean of 75 and a standard deviation of 8. What is the z-score of the data point? Round to the nearest hundredth.

QUESTION 8 A data point is taken from a normal distribution that has a mean of 15.4 and a standard deviation of 0.25. If the z-score of the data point is -1, then what is the value of the data point? Round to the nearest tenth

QUESTION 9 A normal distribution for weights of filled cereal boxes has a mean of 17.98 ounces and a standard deviation of 0.1144 ounces. What is the z-score for the weight of 17.91 ounces? Round to the nearest hundredth

QUESTION 10 A data point is taken from a normal distribution that has a mean of 99 and a standard deviation of 0.4. If the z-score of the data point is 2.57, then what is the value of the data point? Round to the nearest hundredth.

QUESTION 11 Use your TI83 (or Excel): A normally distributed population has a mean of 77 and a standard deviation of 15. Determine the probability that a random data has a value of less than 74. Round to four decimal places.

QUESTION 12 Use your TI83 (or Excel): A normally distributed population has a mean of 77 and a standard deviation of 12. Determine the probability that a random data has a value between 72 and 80. Round to four decimal places.

QUESTION 13 Use your TI83 (or Excel): A normally distributed population has a mean of 74 and a standard deviation of 18. Determine the probability that a random data has a value between 71 and 82. Round to four decimal places.

QUESTION 14 Use your TI83 (or Excel): A normally distributed population has a mean of 72 and a standard deviation of 20. Determine the probability that a random data has a value between 74 and 81. Round to four decimal places.

QUESTION 15 Use your TI83 (or Excel): A normally distributed population has a mean of 79 and a standard deviation of 14. Determine the probability that a random data has a value of less than 77. Round to four decimal places.

You’ve been asked to carry out a quantitative analysis of your company’s marketing campaign, and have been given permission to gather all the data you believe necessary. Drawing on all the material covered what strategies will you employ to carry out this task? Identify the variables you would collect and the types of statistical analyses you would use.

PLEASE WRITE CLEAR!

Let x represent the dollar amount spent on supermarket impulse buying in a 10-minute (unplanned) shopping interval. Based on a certain article, the mean of the x distribution is about $31 and the estimated standard deviation is about $8. (a) Consider a random sample of n = 70 customers, each of whom has 10 minutes of unplanned shopping time in a supermarket. From the central limit theorem, what can you say about the probability distribution of x, the average amount spent by these customers due to impulse buying? What are the mean and standard deviation of the x distribution? The sampling distribution of x is not normal. The sampling distribution of x is approximately normal with mean μx = 31 and standard error σx = $0.11. The sampling distribution of x is approximately normal with mean μx = 31 and standard error σx = $8. The sampling distribution of x is approximately normal with mean μx = 31 and standard error σx = $0.96. Is it necessary to make any assumption about the x distribution? Explain your answer. It is not necessary to make any assumption about the x distribution because μ is large. It is necessary to assume that x has a large distribution. It is necessary to assume that x has an approximately normal distribution. It is not necessary to make any assumption about the x distribution because n is large. (b) What is the probability that x is between $29 and $33? (Round your answer to four decimal places.) (c) Let us assume that x has a distribution that is approximately normal. What is the probability that x is between $29 and $33? (Round your answer to four decimal places.) (d) In part (b), we used x, the average amount spent, computed for 70 customers. In part (c), we used x, the amount spent by only one customer. The answers to parts (b) and (c) are very different. Why would this happen? The standard deviation is smaller for the x distribution than it is for the x distribution. The x distribution is approximately normal while the x distribution is not normal. The sample size is smaller for the x distribution than it is for the x distribution. The mean is larger for the x distribution than it is for the x distribution. The standard deviation is larger for the x distribution than it is for the x distribution. In this example, x is a much more predictable or reliable statistic than x. Consider that almost all marketing strategies and sales pitches are designed for the average customer and not the individual customer. How does the central limit theorem tell us that the average customer is much more predictable than the individual customer? The central limit theorem tells us that small sample sizes have small standard deviations on average. Thus, the average customer is more predictable than the individual customer. The central limit theorem tells us that the standard deviation of the sample mean is much smaller than the population standard deviation. Thus, the average customer is more predictable than the individual customer.