An automotive center keeps track of customer complaints received each week.  The probability distributions of complaints are shown below.  The random variable, xi, represents the number of complaints, and p(xi) is the probability of receiving xi complaints for two of the stores. The cost impact of each complaint is believed to be y=$10x3 where x is the number of complaints. Store A xi 0 1 2 3 4 5 6 p(xi) 0.10 0.15 0.20 0.25 0.15 0.10 0.05     Store B             xi 0 1 2 3 4 5 6 p(xi) 0.10 0.15 0.25 0.22 0.13 0.08 0.07 The Manager provides the following utility function to evaluate the two stores. xi 0 1 2 3 4 5 6 u(xi) 1.00 0.60 0.40 0.20 0.10 0.05 0.00 Which store does the Manager prefer as having fewer complaints? Compare using utility as the metric with using the average number of complaints as the criterion for deciding which Store is better (or worse). Why?

Neighborhood Insurance sells fire insurance policies to local homeowners. The premium is $150, the probability of a fire is 0.1%, and in the event of a fire, the insured damages (the payout on the policy) will be $140,000. g. What are the expected value and variance of your profit?

Tiffany is a manager who needs to fire the worst performing 3% of employees. At her organization, employee performance is a normally distributed variable. Tiffany should fire employees who have a performance score that correspond with a z-score less than or equal to _____

The annual premium for a $20,000 insurance policy against the theft of a painting is $350. If the (empirical) probability that the painting will be stolen during the year is 0.02, what is your expected return from the insurance company if you take out this insurance? Let X be the random variable for the amount of money received from the insurance company in the given year. E(X)= dollars

A student must have a B average or better for all courses to qualify for any athletic team at Jefferson High School. The table below shows the distribution of students' grades in three sports at the school. Students with Students with a Sport an A Average B Average Field hockey 15 4 Basketball 7 13 Football 2 22

When practicing basketball, Rachel has a 67% chance of making a free throw. She shoots 12 free throws. Let the random variable X be the number of free throws she makes. Find the probability she makes exactly 5 free throws. Give your answer to at least three nonzero decimal places. What is the expected value of X. Interpret this value.

An automotive center keeps track of customer complaints received each week.  The probability distributions of complaints are shown below.  The random variable, xi, represents the number of complaints, and p(xi) is the probability of receiving xi complaints for two of the stores. The cost impact of each complaint is believed to be y=$10x3 where x is the number of complaints. Store A xi 0 1 2 3 4 5 6 p(xi) 0.10 0.15 0.20 0.25 0.15 0.10 0.05     Store B             xi 0 1 2 3 4 5 6 p(xi) 0.10 0.15 0.25 0.22 0.13 0.08 0.07   Compute the simulated averages and standard deviations of the number of complaints per week for each store and the total for both stores over the 52 weeks. Compare to the theoretical mean and standard deviations.

Please assist.

A survey was conducted two years ago asking college students their top motivations for using a credit card. To determine whether this distribution has changed, you randomly select 425 college students and ask each one what the top motivation is for using a credit card. Can you conclude that there has been a change in the claimed or expected distribution? Use a=0.10. Complete parts (a) through (d). New Survey Frequency, f 111 97 Response Old Survey % Rewards 29% 23% Low rates Cash back Discounts Other 22% 108 8% 46 18% 63 UD. XX O D. X Xo 2 OC. X >Xo OC. X>x (c) Calculate the test statistic. (Round to three decimal places as needed.) %3D (d) Decide whether to reject or fail to reject the null hypothesis. Then interpret the decision in the context of the original claim. V the claimed or ▼enough evidence to conclude that the distribution of motivations Ho At the 10% significance level, there expected distribution.

Part 2 Let x be a random variable that represents the batting average of a professional baseball player. Let y be a random variable that represents the percentage of strikeouts of a professional baseball player. A random sample of n = 6 professional baseball players gave the following information. x 0.338 0.306 0.340 0.248 0.367 0.269 y 3.5 7.7 4.0 8.6 3.1 11.1  Σx = 1.868, Σy = 38, Σx2 = 0.592034, Σy2 = 294.32, Σxy = 11.1556, and r ≈ -0.901. Se ≈ 1.5890, a ≈ 26.420, and b ≈ -64.517. (a) Find the predicted percentage  of strikeouts for a player with an x = 0.328 batting average. (Use 2 decimal places.) %(b) Find a 90% confidence interval for y when x = 0.328. (Use 2 decimal places.) lower limit  % upper limit  %