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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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7.2 K HW Score: 96.07%, 26.9 of 28 points Points: 0.5 of 1 The accompanying frequency distribution summarizes sample data consisting of ages of randomly selected inmates in federal prisons. Use the data to construct a 95% confidence interval estimate of the mean age of all inmates in federal prisons. GOODB Age (years) 16-25 26-35 36-45 46-55 56-65 Over 65 Using the class limits of 66-75 for the "over 65" group, find the confidence interval. με (Round to one decimal place as needed.) Save Number 12 60 65 37 13 4 0
2. We wish to analyze the monthly water usage of a production plant, Y (in gallons), with respect to its monthly production X₁ (in tons), mean monthly temperature X₂ (in °F) and the monthly number of days X3 of plant operation using the data given in the file 'WATER.xlsx'. The following models are considered: I: II: Y = Y = Bo + B₁X₁ + B₂X2 + ß3X3 + E, Bo + B₁X₁ + B2X2 + B3X3 + B₁X1X2 + B5X₁X3 + B6X2X3 + ε Perform your tests at a = 10% in this question. (a) Generate a matrix scatter plot and state the relationship among these variables. (b) Use R/Minitab to estimate the parameters of Model I, set up three hypotheses to test whether each variable is useful given that the other variables are in the model. (c) In Model II, the interaction terms among these three variables are considered. Using the sum of squared residuals from the estimates of models I and II, do an F-test to test the whether all these interaction terms are useful jointly in predicting the monthly water usage of the…
The computation of the various SS terms can be viewed as a two-step effort. Explain it.
Price SqFt 600000 2767 545000 2731 314900 2051 419000 2084 365000 2270 479000 1950 323000 1235 339900 2116 399000 1644 552000 2415 223017 1375 315777 1529 499000 2223 575000 2327 342000 1879 375000 1558 349000 2012 485000 1200 549888 1410 295000 1943 399000 1827 306999 1840 265200 1636 479000 2357 249700 1152 539500 2650 365000 2154 295900 1279 499000 2156 526000 2493 514900 2390 346000 1347 460000 2120 389000 1917 499000 1200 405000 2643 389900 1789 545000 2327 339000 1742 425000 1746 479000 1421 392000 2569 Interpret b0 in the context of this problem. Interpret b1 in the context of this problem. What percent of total variation in prices is explained by the regression model? Provide evidence to support your answer. Please include the excel function.
i really need help with question number 2
11.15 only
Zip Code 93905 93905 93905 93905 93905 93905 93905 93905 93905 93905 93905 93905 93905 93905 405 93905 760 4 93905 630 4 93905 from ho 640 ales above, 3 93905eath ip 749 find: sampl 4 93905 503 3 93905 43908 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 93906 Price 714 855 598 769 529 795 715 635 989 93901 93901 93901 93901 790 605 800 480 660 799 900 799 640 650 93906 do the 1069 93906 700 93906 819 635 850 840 625 730 728 840 845 785 700 609 739 685 675 565 595 Bedrooms 3 5 3 4 2 5 3 4 6 4 3 5 3 2 3 3 4 6 3 3 2 4 3 4 3 4 4 3 4 4 4 3 2 3 3322 Baths 1 3 3 3 1 3 2 3 3 3 1 3 1 1 3 2 13 abd 3 1 3 3 2 3 3 2 2 2 3 2 3 2 3 3 2 3 3 3 3 2 3 2 2 1 1 Square Feet 821 2658 1638 2607 729 2253 1529 1980 3074 2607 948 2076 1089 863 2255 1353 1442 1837 920 2450 1877 1231 2191 3043 1814 1498 1240 2905 1328 2195 1112 2156 2276 1450 2400 2191 2207 1852 1077 1501 1152 1420 816 1212
Suppose automobile insurance companies gave annual premiums for top-rated companies in several states. The figure below shows box plots for the annual premium for urban customers in three states. Which state has the smallest interquartile range?
A passcode contains four digits from the digits 0-9. How many different passcodes can be made if no digits is used more than once?
987987867x5667780897766x46567788907x687898765x5
Price SqFt 600000 2767 545000 2731 314900 2051 419000 2084 365000 2270 479000 1950 323000 1235 339900 2116 399000 1644 552000 2415 223017 1375 315777 1529 499000 2223 575000 2327 342000 1879 375000 1558 349000 2012 485000 1200 549888 1410 295000 1943 399000 1827 306999 1840 265200 1636 479000 2357 249700 1152 539500 2650 365000 2154 295900 1279 499000 2156 526000 2493 514900 2390 346000 1347 460000 2120 389000 1917 499000 1200 405000 2643 389900 1789 545000 2327 339000 1742 425000 1746 479000 1421 392000 2569 Can square feet explain prices? Provide evidence to support your answer. If the square feet is 2418, what is the expected price for the home? Please include the excel function.
***ONLY QUESTION 6*** House prices are $1,000 each