TABLE A-6 Critical Values of the Pearson Correlation Coefficient r a = .05 a = .01 4. .950 .999 5. .878 .959 6. .811 .917 .754 .875 .707 .666 criticel 8. 834 9. .798 value for... 10 .632 .765 11 .602 .735 a =.01 12 .576 .708 13 .553 .684 14 .532 .661 15 .514 .641 2.n=92 a=105 16 .497 .623 17 .482 .606 .468 456 .590 .575 18 19 561 505 .463 20 .444 .396 .361 335 25 30 35 .430 40 .312 .402 45 294 .378 50 .279 .361 60 .254 .330 70 .236 .220 .305 .286 80 90 .207 .269 100 .196 .256 NOTE:To test Ho: p = 0 against H: p # 0, reject Ho if the absolute value of r is greater

A researcher is investigating a new screening tool that is intended to help prevent the onset of breast cancer in young women. Suppose he tests the new device on a group of 10 women. The following table shows the test result and true breast cancer status of each of the women. What can we say about the new device with regards to its accuracy?     Patient Test Result True Cancer Status A + + B + + C + - D + - E - + F - + G + - H - + I - - J + -

How do I find the relative extrema of x3 - 27x?

A researcher wants to investigate the relationship between the hours a student spends studying for a test and the score on the test. The following data is gathered: Hours (x) 20 16 34 23 27 32 18 22 Score (y) 6.5 8.5 7 9.5 7.5 8 Annual (X-X) salary, $1000 Years of (Y-Y) (X-X)(Y-Ÿ) (X-X)? (Y-7)² schooling 20 6.5 -4 -1.25 16 1.5625 16 6. -8 -1.75 14 64 3.0625 34 8.5 10 0.75 7.5 100 0.5625 23 7 -1 -0.75 0.75 1 0.5625 27 3 1.25 3.75 9. 1.5625 32 9.5 8. 1.75 14 64 3.0625 18 7.5 -6 -0.25 1.5 36 0.0625 22 8 -2 0.25 -0.5 4 0.0625 192 62 46 294 10.5 Calculate: a. The regression line of y based on x. b. The estimated test score for a person who studied 28 hours.

Consider the following model of a market for hats in which Qs is quantity of hats produced, Qd is quantity of hats purchased and P is the price of a hat.  Qs=5+12P Qd=50-3P if production conditions change so that Qs=-10+12P, what will be the change in Q*? compared to the value 41, such that Q*=Qs=Qd remains true? a. 4 b. -3 c. -4 d. 3

How do I solve this problem? I'm not sure what to do.

Can someone walk me through how to find this using excel? I am studying for my final and I am so lost on the first one. The PowerPoint from class is not helping either

The Organization for Economic Cooperation and Development (OECD) consists of 20 industrialized countries. For these nations, the prediction equation relating y = child poverty rate (in percentage points) to x = social expenditure as a percentage of gross domestic product (GDP) is  = 22-1.3x. In 2000, the actual child poverty rate ranged from 2.8% (in Finland) to 21.9% (in the U.S.). Social expenditure as a percentage of GDP ranged from 2% (in the United States) to 16% (in Denmark). What is the value of the slope (b) estimated in the linear prediction equation provided above (= 22-1.3x)?  Also, interpret the slope.   Estimated slope (b):     Interpretation of slope:

A quality control engineer studied the relationship between years of experience as a system control engineer and the capacity of the engineer to complete within a given time a complex control design including the debugging of all computer programs and control devices. A group of 25 engineers having widely differing amounts of experience (measured in months of experience) was given the same control design project. The results of the study are given in the following table with y 5 1 if the project was successfully completed in the allocated time and y 5 0 if the project was not successfully completed. a. Determine whether experience is associated with the probability of completing the task. b. Compute the probability of successfully completing the task for an engineer having

Please answer quickly and correctly The Samsung plant in Newberry is an assembly plant for home appliances. They assembly three types of appliances including washing machine, dishwasher, and oven (reference by W, R, and O). Each type of appliance is produced in a different assembly line which has some amount of output per day. Let’s imagine a quality engineer has gathered the following data in Table 1 from a small period of production, counting the number of products with defects and without defects. Let D indicates a defective product and ND indicates not defective. Washing Machine Dishwasher Oven: Defective 5 2 15 Not defective 63 86 45 Table 1: Number of products with and without defects by type a. Overall, what is the probability that a randomly selected product is defective? b. What is the probability that a randomly selected product is an oven? c. What is the probability that a product is defective, given it is an oven? d. What is the probability that a product is…