Company Name ProfitsR&D ExpenseSalesAbex1941.6728.4Boeing2256184630184Curtiss-Wright32.71.6179.7GenCorp37361937General Dynamics227663472K&F Industries2914.1782.9Kaman-14.714.1295.5Lockheed54942010100Martin Marietta512.42005954.3McDonnell Douglas108650917373Northrop180935550OEA23.12.688.1Orbital Sciences5.46174.6Pacific Scientific8.18.2172.6Sequa43.817.61868.3Sunstrand130.1115.41672.7Thiokol101.814.21311.7United Technologies200121921641Woodward Governor3316374.2 Based on the regression model generated, forecast profits for a firm with sales revenue of 250.00

In this case, sales revenue is the independent variable and profit is the dependent variable.

Answered: Company Name Profits R&D Expense Sales…

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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a. 5 b. 10 c. 16 d. 21
im.9
A prospective MBA student would like to examine the factors that impact starting salary upon graduation and decides to develop a model that uses program per-year tuition as a predictor of starting salary. Data were collected for 37 full-time MBA programs offered at private universities. The results are displayed in the accompanying table, and the regression equation and other values are provided. Use this information to complete parts (a) through (c) below. Y = -12,195.7+2.4032X; n n Σ Υ = 4,230,133, Σ γ = 520,438,426,235,Σ X,Y, = 234,279,400,152 i=1 i=1 Click the icon to view the data table. Since the value of n O D. It measures the variability in the actual per-year tuition from the predicted number of starting salary. b. Determine the standard error of the estimate. Syx = (Round to two decimal places as needed.) c. How useful do you think this regression model is for predicting starting salary? ₁2 the regression model is is i=1 for predicting starting salary.
***ONLY QUESTION 6*** House prices are $1,000 each
Consider the following table.
Consider the following table.
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How long does it take to finish the 1161-mile Iditarod Dog Sled Race from Anchorage to Nome, Alaska? Finish times (to the nearest hour) for 57 dogsled teams are shown below. 261 271 236 244 279 296 284 299 288 288 247 256 338 360 341 333 261 266 287 296 313 311 307 307 299 303 277 283 304 305 288 290 288 289 297 299 332 330 309 328 307 328 285 291 295 298 306 315 310 318 318 320 333 321 323 324 327 For this problem, use five classes. (a) Find the class width. (b) Make a frequency table showing class limits, class boundaries, midpoints, frequencies, relative frequencies, and cumulative frequencies. (Give relative frequencies to 2 decimal places.)
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Year Population 1790 3,929,214 1800 5,308,483 1810 7,239,881 1820 9,638,453 1830 12,866,020 1840 17,069,453 1850 23,191,876 1860 31,443,321 1870 39,818,449 1880 50,155,783 1890 62,947,714 1900 75,994,575 1910 91,972,266 1920 105,710,620 1930 122,775,046 1940 131,669,275 1950 150,697,361 1960 179,323,175 1970 203,302,031 1980 226,545,805 1990 248,709,873 2000 281,421,906 2010 308,745,538 Use excel to calculate the Least Squares Regression Line for the census data? (need to include correct values for a and b) Using the line, you calculated in number 5, what would you predict the population to have been in 1985? EXPLAIN. Should you use the previously calculated Regression Line to predict population in the year 2200? EXPLAIN.

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Company Name	Profits	R&D Expense	Sales
Abex	194	1.6	728.4
Boeing	2256	1846	30184
Curtiss-Wright	32.7	1.6	179.7
GenCorp	37	36	1937
General Dynamics	227	66	3472
K&F Industries	29	14.1	782.9
Kaman	-14.7	14.1	295.5
Lockheed	549	420	10100
Martin Marietta	512.4	200	5954.3
McDonnell Douglas	1086	509	17373
Northrop	180	93	5550
OEA	23.1	2.6	88.1
Orbital Sciences	5.4	6	174.6
Pacific Scientific	8.1	8.2	172.6
Sequa	43.8	17.6	1868.3
Sunstrand	130.1	115.4	1672.7
Thiokol	101.8	14.2	1311.7
United Technologies	200	1219	21641
Woodward Governor	33	16	374.2