Hospital Length of Stay (months) for 16 Patients 1 10.5 10.0 2 4.5 2.0 3 7.5 4.0 4 12.0 11.0 5 7.5 11.0 6 9.0 11.0 7 6.0 6.5 8 5.0 5.0 9 6.0 8.0 10 12.0 16.0 11 7.0 6.5 12 4.5 6.0 13 3.5 3.5 14 6.0 10.0 15 7.5 7.0 16 3.0 5.5 Obtain the regression equation Calculate R2

Hospital Length of Stay (months) for 16 Patients 1 10.5 10.0 2 4.5 2.0 3 7.5 4.0 4 12.0 11.0 5 7.5 11.0 6 9.0 11.0 7 6.0 6.5 8 5.0 5.0 9 6.0 8.0 10 12.0 16.0 11 7.0 6.5 12 4.5 6.0 13 3.5 3.5 14 6.0 10.0 15 7.5 7.0 16 3.0 5.5 Obtain the regression equation Calculate R2

College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter4: Polynomial And Rational Functions

Section4.6: Rational Functions

Problem 11SC: Find the mean hourly cost when the cell phone described above is used for 240 minutes.

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Find the mean hourly cost when the cell phone described above is used for 240 minutes.
15.57/0.3
1. DETAILS PECKSTAT2COREQ 9.R.084.S. MY NOTES In a survey on supernatural experiences, 728 of 4,003 adult Americans surveyed reported that they had seen a ghost. Assume that this sample is representative of the population of adult Americans. (a) Use the given information to estimate the proportion of adult Americans who would say they have seen a ghost. (Round your answer to three decimal places.) (b) Verify that the conditions for use of the margin of error formula to be appropriate are met. Select---v. The condition that the The condition that the sample is a random sample from the population of interest or the sample is selected in a way that should result in a representative sample is sample size is large is ---Select--- v. (c) Calculate the margin of error. (Round your answer to three decimal places.) (d) Interpret the margin of error in context. O It is unlikely that the estimated proportion of all adult Americans who would say they have seen a ghost differs from the true…
Price_($000)/Sq Ft 1/Sq Ft Location 14.0542 0.0653 0 17.2907 0.0524 0 18.3029 0.00649 0 15.7341 0.04374 0 14.8521 0.01913 0 15.3572 0.0197 0 18.3278 0.01583 0 15.8483 0.41563 0 17.392 0.29976 0 15.8826 0.1798 0 15.5492 0.00816 0 14.619 0.0325 0 15.7633 0.21829 0 15.1289 0.015939 0 17.2874 0.18765 0 15.6938 0.00986 0 15.3672 0.03096 0 15.3126 0.01917 0 17.4008 0.06055 0 16.1066 0.0611 0 16.6637 0.1171 1 16.5504 0.05552 1 17.0575 0.00657 1 17.9466 0.1407 1 17.8913 0.0648 1 15.5396 0.03339 1 18.6629 0.03443 1 18.0774 0.019 1 20.8122 0.20162 1 18.3237 0.319 1
x1: Rate of hay fever per 1000 population for people under 25 96, 92, 122,126, 94, 123,12, 93, 125, 95, 125, 117, 97, 122,127, 88 x2: Rate of hay fever per 1000 population for people over 5097, 112,103, 96,114, 88, 110, 79, 15, 100, 89, 114, 85, 96 x1 = s1 = x2 = s2 = Compute the corresponding z or t-value as appropriate. (Test the difference ?1 − ?2. Do not use rounded values. Round your answer to three decimal places.) What is the value of the sample test statistic? Find a 90% confidence interval for ?1 − ?2. (Round your answers to two decimal places.)lower limit:________upper limit:________
Determine the number of significant digit/s in the following numbers: 1. 3.0800 2. 0.00418 3. 3.461728 + 14.91 + 0.980001 + 5.2631 4. 0.04216 – 0.0004134 5. 2.8723 x 1.6 (6305) 6. (0.010)
The following data show the lengths of boats moored in a marina 16,17,19,20,20,21,23,24,25,25,26,26,27,27,27,28,29,30,32,33,34,35,37,39 40 Fill in the blank. Around a and b to the hundredths place x(repeating)= S= Create 75% Chebyshevs interval (_,_)
2.1970, 3.5952, 1.6856, 0.9327, 0.4176, 1.7347, 1.9638, 2.3582, 1.1870, 0.5700, 1.4206, 1.2499, 1.9973, 1.8797 Mean = Error = Standard deviation = Uncertainty =
3-7. Write each answer with the correct number of significant figures (a) 1.02.1 + 3.4 + 5.8 12.300 0 (b) 106.9 31.4 (c) 107.868 (2.113 X 75.500 0 102(5.623 x 10 5 519.568 (d) (26.14/37.62) X 4.38 3.043 413 10 (e) (26.14/(37.62 x 10)) x (4.38 x 10 2) 3.043 413 x 10 11.933 7 (f) (26.14/3.38) + 4.2 (g) log(3.98 x 10*) = 4.897 79 X 10 4.599 9 (h) 10-6.31
Question 1: The amount of time until an accident occurs at an industrial facility follows an exponential distribution with mean 40 days. a) What is the probability that the next accident occurs between 50 and 100 days? b) What is the probability that the time until an accident occurs exceeds the mean time by more than 2 standard deviations? c) Suppose it has been at least 30 days with no accidents. What is the probability that it will be at least 80 days until an accident occurs?
What is the most frequent number of over-the-limit items for this data set? ans = What is the frequency of the most frequent number of over-the-limit items? ans =
Time for pizza delivery by a certain restaurant follows a uniform distribution and can range from 20 to 45 minutes. 60% of the time, the delivery time will fall above what value?