For these binomial settings, give the parameters n and p. a) Orchid flowers can be “left-handed” or “right-handed” depending on the position of certain structures. 25% of flowers are left-handed. In a sample of 18 orchid flowers from separate plants, we count the number of left-handed flowers. n = ____________ p = _______________

b) When a tall pea plant is crossed with a dwarf pea plant, Medelian genetics predict that 3/4ths of the offspring will be tall (the gene for dwarfism is recessive). Such a cross produced 10 offspring; we will count how many are tall plants. n = ____________ p = _______________

c) A recent study from the American Enterprise Institute found that only 26% of poor adults ages 18 to 55 are married. We select a random sample of 60 (independent) adults with incomes below the poverty threshold, and ask them if they are married. n = ____________ p = _______________

What is multiple R, R square, & Adjusted R square?

Do regression model results indicate significance, meaning the results can be accepted? Yes or No.

For every 1 increase in Temperature, how much do sales increase?

The following data are the heights of fathers and their sons in inches. The father's height is his height when he was the same age as the son.

a. A geneticist might wonder if there is a tendency for tall fathers to have tall sons and short fathers to have short sons. Answer this question by computing the appropriate statistic and testing it for statistical significance. (Hint: The statistic will be much easier to compute if you subtract 40 from each of the scores. Doing so will not affect the value of the statistic.)

b. Can you use the height of a father to predict the height of his son? Compute the regression equation for predicting sons’ heights from fathers’ heights. Use this equation to predict the height of a son whose father is 46 inches tall.

c. If you had a father who had a height of 25" when he was the same age as his son, should you use the regression equation to predict the son’s height? Why or why not?

d. An environmentalist might wonder if there is a tendency for generations to get taller. Are sons taller than their fathers were at the same age? What statistical test would be most appropriate for answering this question. (Hint: You will need to recall some previous lessons to get this one correct.)

An evaluation was recently performed on brands and data were collected that classified each brand as being in the technology or financial institutions sector and also reported the brand value. The results in terms of value​ (in millions of​ dollars) are shown in the accompanying data table. Complete parts​ (a) through​ (c).

A) Assuming the population variances are​ equal, is there evidence that the mean brand value is different for the technology sector than for the financial institutions​ sector? (Use α=0.05​.) Determine the hypotheses. Let μ1 be the mean brand value for the technology sector and μ2 be the mean brand value for the financial institutions sector. Choose the correct answer below

-Find the test statistic

-Find the p-Value

b. Repeat​ (a), assuming that the population variances are not equal.

c. Compare the results of​ (a) and​ (b).

The data in the table, from a survey of resort hotels with comparable rates on Hilton Head Island, show that room occupancy during the off-season (November through February) is related to the price charged for a basic room.

• First make a linear equation using linear regression on your calculator where x = price and y = occupancy rate.
• Convert occupancy rate to quantity of rooms in a 200-room hotel.
• Write down a revenue function for a 200-room hotel.
• What price per day will maximize the daily off-season revenue for a typical 200-room hotel? Use Calculus to determine the maximum.
• If this 200-room hotel has daily operating costs of $5510 plus $30 per occupied room. What price will maximize the daily profit during the off-season? Again use calculus to determine the maximum

More detailed instructions are given on page 690 of the textbook (12th edition).

2. Use the methods below to normalize the following group of data: 150, 800, 640, 290, 2800

(a)min-max normalization by setting min = 0 and max = 1

(b) z-score normalization

(c) normalization by decimal scaling

A manager is looking at the number of sick days used by employees in a year.

H0: the average number is 8 or below

H1: the average is over 8

We know that the standard deviation of the number of sick days used by employees is 2, and we want to test at 10% significance level.

Say we took a random sample of 50 employees, and checked their records, and found that the average was 8.1

The manager figures that the critical value (z-sub-0.1) is 1.28.

What should be the decision?

A new vaccine developed by Very Bad Drug Corp is about to be distributed en masse in a Third World country experiencing an epidemic. The vaccine either does nothing or is effective in preventing the disease. The country's leadership doesn't trust First World drug companies and wishes to avoid making the mistake of "believing the drug works when in fact it does nothing". What sort of mistake is this? If you were in charge would you have any tools at your disposal to reduce the possibility of making this error with your current knowledge?

State University offers several sections of a Business Statistics course in an in-class and online format. Both formats are administered the same final exam each year. You have been assigned to test the hypothesis that the average final exam score of in-class students is different from the average final exam score of online students. The following data summarizes the sample statistics for the final exam scores for students from each format. Assume that the population variances are unequal. In-class Format Online Format Sample mean 86.5 84.7 Sample size 22 25 Sample standard deviation 4.6 6.1 If Population 1 is defined as in-class format and Population 2 is defined as online format, and using LaTeX: \alpha α = 0.05, the conclusion for this hypothesis test would be because the absolute value of the test statistic is ______________________________________________________________. less than the absolute value of the critical value, you can conclude that the average final exam score of in-class students is equal to the average final exam score of online students less than the absolute value of the critical value, you cannot conclude that the average final exam score of in-class students is different from the average final exam score of online students more than the absolute value of the critical value, you cannot conclude that the average final exam score of in-class students is different from the average final exam score of online students more than the absolute value of the critical value, you can conclude that the average final exam score of in-class students is different from the average final exam score of online students

You are interested in finding a 90% confidence interval for the average commute that non-residential students have to their college. The data below show the number of commute miles for 11 randomly selected non-residential college students. Round answers to 3 decimal places where possible. 25 21 26 6 25 14 26 24 7 10 14 a. To compute the confidence interval use a distribution. b. With 90% confidence the population mean commute for non-residential college students is between and miles. c. If many groups of 11 randomly selected non-residential college students are surveyed, then a different confidence interval would be produced from each group. About percent of these confidence intervals will contain the true population mean number of commute miles and about percent will not contain the true population mean number of commute miles.

Several years ago a well-known public official left Illinois and moved to Texas.  A local regional reporter revealed both his regional chauvinism and his feelings about the official when he remarked that “on this occasion he raised the mean IQ in both states”.

Such a statistical change is possible. Explain how.

Considering this, and since the mean IQ of the US is the average of the means of all the states, it appears that by a mere reshuffling of populations between states, one could increase the mean IQ of the U.S! Is this so? Explain.

Discuss a management decision-making perspective for Index numbers with detailed examples.

Q1: Estimate the absolute standard deviation and the coefficient of variation for the results of the following calculations. Round to the correct number of significant figures. The numbers in parenthesis are absolute standard deviations.

1. y =5.75(±0.03) + 0.833(±0.001) – 8.021(±0.001) = -1.4381
2. y =18.97(±0.04) + .0025(±0.0001) +2.29(± .08)= 21.2625
3. y =66.2(±.3) x 1.13(±.02) x10^-17 = 7.4806x10^-16
4. y =251(±1) x 860(±2) / 1.673(±.006) = 129025.70
5. y = [157(±6) - 59(±3)] / [1220(±1) + 77(±8)] = 7.5559x10^-2
6. y = 1.97(±.01) / 243(±3) = 8.106996x10^-3

1. A psychologist would like to estimate the average IQ of Canadians. (IQ scores are known to follow a normal distribution with standard deviation 15.) She takes a sample of 49 Canadians and measures a sample mean IQ of 107.34 and a sample standard deviation of 17.36.

(a) Use the information above to calculate a 92% confidence interval to estimate the average IQ of Canadians.

(b) Interpret the confidence interval obtained in part (a).

(c) Suppose the researcher also wishes to test the hypotheses
H0 :μ=103 vs. μ̸=103

at the 0.08 significance level. Is this possible to do with the confidence interval calculated in part (a)? If so, what is the correct conclusion? If not, why not?

(d) Suppose the researcher also wishes to test the hypotheses
H0 :μ=105 vs. μ>105

at the 0.08 significance level. Is this possible to do with the confidence interval calculated in part (a)? If so, what is the correct conclusion? If not, why not?

The Dean of the Business School at State University would like to test the hypothesis that no difference exists between the average final exam grades for the Introduction to Marketing course and the Introduction to Finance course. A random sample of eight students who took both courses was selected and their final exam grades for each course are shown below. Student 1 2 3 4 5 6 7 8 Marketing 82 86 74 93 90 76 87 100 Finance 76 91 70 79 96 70 85 81 If Population 1 is defined as the Marketing exam scores and Population 2 is defined as the Finance exam scores, and using LaTeX: \alpha α = 0.05, the conclusion for this hypothesis test would be that because the test statistic is _______________________________________________________. less than the critical value, we can conclude that no difference exists between the average final exam grades for the Introduction to Marketing course and the Introduction to Finance course less than the critical value, we cannot conclude that a difference exists between the average final exam grades for the Introduction to Marketing course and the Introduction to Finance course more than the critical value, we cannot conclude that a difference exists between the average final exam grades for the Introduction to Marketing course and the Introduction to Finance course more than the critical value, we can conclude that a difference exists between the average final exam grades for the Introduction to Marketing course and the Introduction to Finance course