The Precision Machining Company makes hand-held tools on an assembly line that produces one product every minute. On one of the products, the critical quality dimension is the diameter (measured in thousandths of an inch) of a hole bored in one of the assemblies. Management wants to detect any shift in the process average diameter from 0.010 in. Management considers the variance in the process to be in control. Historically, the average range has been 0.002 in., regardless of the process average. Design an x-chart to control this process, with a center line at 0.010 in. and the control limits set at three sigmas from the center line. Management provided the results of 80 minutes of output from the production line, as shown in the table below. During these 80 minutes, the process average changed once. All measurements are in thousandths of an inch. Sample data for Precision Machining Company Diameter (thousandths of an inch) Minutes 1- 12 10 11 13 11 12 10 9. 8 11 12 13 - 24 10 11 12 11…

Suppose the mean and variance of variable X are given respectively by μ = 36.2 and Var(X) =4.2. What is the average of the squared values of variable X?

At age 9 the average weight for both boys and girls are exactly the same. A random sample of 9 year olds gave the following results....                                   Boys:                Girls:Sample Size:               65                     50Mean weight (lbs):      130                   125Pop. Variance:            120                   130 At alpha 0.05, do the data support the claim that there is a difference in heights?

I have asked this question twice and both times it has been wrong.  Answer given F=.82 and .77 both these are incorrect.    A bakery is considering buying one of two gas ovens. The bakery requires that the temperature remain constant during a baking operation. A study was conducted to measure the variance in temperature of the ovens during the baking process. The variance in temperature before the thermostat restarted the flame for the Monarch oven was 3.3 for 22 measurements. The variance for the Kraft oven was 4 for 25 measurements. Does this information provide sufficient reason to conclude that there is a difference in the variances for the two ovens? Assume measurements are normally distributed and use a 0.02 level of significance.

Snow avalanches can be a real problem for travelers in the western United States and Canada. A very common type of avalanche is called the slab avalanche. These have been studied extensively by David McClung, a professor of civil engineering at the University of British Columbia. Suppose slab avalanches studied in a region of Canada had an average thickness of u = 67 cm. The ski patrol at Vail, Colorado, is studying slab avalanches in its region. A random sample of avalanches in spring gave the following thicknesses (in cm). 59 51 76 38 65 54 49 62 68 55 64 67 63 74 65 79 (i) Use a calculator with sample mean and standard deviation keys to find x and s. (Round your answers to two decimal places.) X= cm S= cm (ii) Assume the slab thickness has an approximately normal distribution. Use a 1% level of significance to test the claim that the mean slab thickness in the Vail region is different from that in the region of Canada. (a) What is the level of significance? State the null and…

The weight of cereal boxes (y) follows a normal distributed with a variance of 0.1 squared ounces. If the average is 15.8 ounces, then P(y < 16) = If the average is 16.5 ounces, then P(y > 16.2)

Our environment is very sensitive to the amount of ozone in the upper atmosphere. The level of ozone normally found is 7.6 parts/million (ppm). A researcher believes that the current ozone level is not at a normal level. The mean of 1313 samples is 7.2 ppm with a variance of 0.49 Assume the population is normally distributed. A level of significance of 0.02 will be used. Make the decision to reject or fail to reject the null hypothesis.