1 State2 Alaska3 Arkansas4 Colorado5 ConnecticutExercise Time (mins) Life Expectancy (years)48.078.930.075.6Exercise Time and Life Expectancy per State70.079.581.073.080.180.06Delaware45.077.87 Idaho8 Indiana9 lowa10 Maine11 Missouri61.079.134.076.859.079.147.078.4ife Expectancy79.078.077.039.077.012 Montana48.078.876.013 Nebraska52.079.014 New Jersey71.079.675.015 New York75.080.30.010.020.030.040.050.060.070.080.016 Ohio33.076.6Exercise Time1718

You have a table showing states with their average exercise times and life expectancies. Next to the…

Answered: 1 State 2 Alaska 3 Arkansas 4 Colorado…

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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Gender Alcohol Exercise SQI GPA Male Yes 9 15.5 3.85 Male Yes 11 11.0 5.46 Female No 5 11.1 3.28 Female No 6 13.9 2.37 Female Yes 8 9.9 4.63 Male Yes 11 14.5 4.58 Male Yes 9 10.6 4.96 Male Yes 11 15.1 1.02 Female No 8 12.4 4.33 Female Yes 10 11.5 3.96 Male No 8 10.6 5.83 Male Yes 7 11.5 6.12 Male Yes 10 10.8 2.20 Male Yes 11 12.5 2.93 Male Yes 9 16.4 4.52 Female Yes 2 14.1 4.50 Male Yes 8 15.3 1.63 Female No 6 18.0 3.09 Female No 5 9.7 3.92 Male Yes 11 10.5 3.10 Female No 8 13.7 5.42 Male Yes 8 14.9 2.03 Female No 7 10.9 5.90 Male No 10 14.5 3.25 Male Yes 7 11.5 5.21 Female No 9 11.3 3.31 Male Yes 9 11.6 2.51 Male No 10 15.6 3.88 Male Yes…
Entity Year Life expectancy United States 1975 72.333 Saint Barthlemy 1974 66.992 Brazil 1992 67.141 Germany 1965 70.364 British Virgin Islands 2013 78.096 Belgium 2010 80.072 Moldova 1970 65.045 Namibia 1969 52.163 Jamaica 2010 74.038 Puerto Rico 2004 77.16 Mongolia 1970 55.364 Nigeria 1983 46.023 Egypt 2015 71.302 Dominican Republic 1986 65.065 Uruguay 2009 76.603 Turkey 1974 54.741 Tanzania 2019 65.456 American Samoa 1960 66.187 Palestine 1961 49.888 Reunion 1962 57.371 Gambia 1986 50.577 South Sudan 2004 51.095 Georgia 1959 63.248 Netherlands 1996 77.642 Macao 2002 80.87 Germany 1984 74.074 Cameroon 2001 51.222 United Kingdom 2014 80.978 Japan 1998 80.656 South Sudan 2009 54.219 Greenland 1980 63.063 Vietnam 1951 52.262 Singapore 1977 70.828 Israel 1983 74.755 Bangladesh 1976 49.402 United Arab Emirates 1991 72.208 United Kingdom 1992 76.111 Costa Rica 1960 60.381 Morocco 1995 66.846 Belgium 1986 74.867…
Monthly Sales 6267.19 7058.06 7119.5 7147.18 7198.52 7298.09 7325.7 7335.68 7355.97 7481.05 7490.23 7530.08 7616.09 7682.69 7684.14 7704.12 7704.98 7779.28 7798.23 7815.15 7844.16 7890.21 7977.6 7993.16 8021.03 8028.37 8068.86 8082.42 8096.17 8119.25 8129.21 8190.68 8255.28 8282.44 8376.31 8392.4 8400.95 8451.16 8456.66 8505.35 8539.25 8543.65 8573.05 8641.78 8667.48 8751.08 8777.97 8800.08 8888.65 8907.03 9096.87 9241.74 9411.68 9450.73 9484.62 9514.57 9521.4 9524.91 9733.44 10123.24 Given the company’s performance record and based on the empirical rule of normal distribution (also known as the 68%-95%-99.7% rule), what would be the lower bound of the range of sales values that contains 68% of the monthly sales? What would be the upper bound of the range of sales values that contains 68% of the monthly sales?
Hotel Overall Comfort Amenities In-House Dining Muri Beach Odyssey 94.3 94.5 90.8 97.7 Pattaya Resort 92.9 96.6 84.1 96.6 Sojourner’s Respite 92.8 99.9 100.0 88.4 Spa Carribe 91.2 88.5 94.7 97.0 Penang Resort and Spa 90.4 95.0 87.8 91.1 Mokihana Hōkele 90.2 92.4 82.0 98.7 Theo’s of Cape Town 90.1 95.9 86.2 91.9 Cap d’Agde Resort 89.8 92.5 92.5 88.8 Spirit of Mykonos 89.3 94.6 85.8 90.7 Turismo del Mar 89.1 90.5 83.2 90.4 Hotel Iguana 89.1 90.8 81.9 88.5 Sidi Abdel Rahman Palace 89.0 93.0 93.0 89.6 Sainte-Maxime Quarters 88.6 92.5 78.2 91.2 Rotorua Inn 87.1 93.0 91.6 73.5 Club Lapu-Lapu 87.1 90.9 74.9 89.6 Terracina Retreat 86.5 94.3 78.0 91.5 Hacienda Punta Barco 86.1 95.4 77.3 90.8 Rendezvous Kolocep 86.0 94.8 76.4 91.4 Cabo de Gata Vista 86.0 92.0 72.2 89.2 Sanya Deluxe 85.1 93.4 77.3 91.8
Wins Attendance (In Millions) 65 2.06 91 2.51 66 1.73 89 3.05 75 3.06 88 2.19 91 2.06 69 1.39 83 2.88 81 2.46 80 1.54 76 2.33 67 1.62 80 3.25 80 3.56 77 2.78 94 3.22 79 2.56 95 3.77 81 1.42 97 3.65 57 1.61 90 2.13 92 3.04 61 2.09 86 3.3 96 1.84 90 2.51 85 1.63 69 1.83 Draw a scatter diagram depicting the correlation between the two variables. Determine the correlation coefficient between the two variables using Excel. Present a regression output between a dependent and one independent variable. Obtain estimated coefficients and R-squared and interpret them. Write a short report on the findings.
Time Spent Studying and Social Media
Score GPA Hours Absences Gender78 3.15 3.0 4 Female75 2.71 4.0 1 Female79 3.57 3.5 2 Male85 3.26 6.5 0 Female85 3.75 2.0 0 Female84 3.20 4.5 3 Female85 3.16 5.0 3 Male80 3.35 1.5 0 Female74 2.75 3.5 6 Male81 3.04 6.5 1 Male76 2.53 3.0 0 Female85 2.92 6.0 1 Male
A researcher hypothesizes that ambient air carbon monoxide pollution levels at a certain location should be higher in the winter than they are in the summer. The reasoning behind this hypothesis is that a major source of carbon monoxide in the air is from the incomplete combustion of fuels, and fuels tend to burn less efficiently at low temperatures. Moreover, it is felt that the stagnant winter air is more likely to trap the pollution. In order to investigate this hypothesis, the data set in DS 9.7.12 is collected which shows the ambient air carbon monoxide pollution levels (parts per million) for ten Sunday mornings in the middle of winter and ten Sunday mornings in the middle of summer.
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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