The population of a particular town changes over time, as shown in the following table. Year 1980, 1982,1984,1988,1992,1996,2000,2002,2008,2012,2016,2020 Population 14,782, 14,567, 14,251, 13,911, 13,566, 13,349, 13,325, 13,330, 13,601, 13,782, 14, 294, 14,619 Based on a quadratic model of the data, what is the predicted population of the town in the year 2024?

The population of a particular town changes over time, as shown in the following table. Year 1980, 1982,1984,1988,1992,1996,2000,2002,2008,2012,2016,2020 Population 14,782, 14,567, 14,251, 13,911, 13,566, 13,349, 13,325, 13,330, 13,601, 13,782, 14, 294, 14,619 Based on a quadratic model of the data, what is the predicted population of the town in the year 2024?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

5. The graph below shows the LFPR for 25-54 year old men over several decades. Percent 100 May-16 98 96 94 92 90 88 86 1948 1954 1960 1966 1972 1978 1984 1990 1996 2002 2008 2014 Source: Bureau of Labor Statistics, Current Population Survey; CEA calculations. (Source: Voxeu.org) It shows that the fraction of these "prime working age men" who are NOT in the labor forced has a. doubled b. tripled c. quadrupled d. not changed
The table shows the leading causes of death in a certain country in a recent year. The population of the country was 311311 million. If you lived in a typical city of 500,000, how many people would you expect to die of cancercancer each year? Cause Deaths Cause Deaths Heart disease 596 comma 700596,700 Alzheimer's disease 84 comma 90084,900 Cancer 575 comma 300575,300 Diabetes 73 comma 40073,400 Chronic respiratory diseases 143 comma 100143,100 Pneumonia/Influenza 53 comma 40053,400 Stroke 128 comma 600128,600 Kidney disease 45 comma 30045,300 Accidents 122 comma 500122,500 Suicide 38 comma 60038,600 About people would be expected to die of cancer each year. (Type a whole number. Round to the nearest person as needed.)
Weight City MPG 3968 20 3583 22 3470 22 3527 23 3990 18 4724 17 3692 21 3315 22 3616 20 5527 14 3719 16 3097 26 3800 19 3532 25 2269 31 5674 15 3402 20 4029 19 3996 19 3242 23 2434 31 2575 29 2960 27 3618 15 4054 19 3192 24 3305 23 3605 19 4240 15 3933 18 3633 19 3790 17 3477 20 3258 21 4685 17 2776 25 2615 24 3186 21 5137 13 3461 21 4233 16 4178 18 4702 17 3713 22 5794 14 2306 28 3194 26 3428 22 4894 12 4751 17 2605 29 3296 25 5267 13 2789 25 3570 19 4011 18 2363 27 4398 15 2806 25 2127 36 2665 27 3419 24 3427 24 3280 25 5765 13 3465 24 2295 30 3038 22 3070 25 4711 17 3230 24 3528 21 4667 16 SUMMARY OUTPUT Regression Statistics Multiple R 0.894328844 R Square 0.799824082 Adjusted R Square 0.797004703 Standard Error 2.238112689…
1. A sales manager would like to see his sales representative’s unit sales per month. The secretary was told to keep a monthly record of the sales. The following are the data from the previous months (in ascending order): 5, 6, 8, 10, 10, 14, 15, 16, 16, 17, 17, 18, 19, 21, 21, 23, 26, 27, 28, 28, 28, 30, 38, 43. Compute for the median and mode. What is the range for the monthly sales?
Calculate the probable population in the year 2010.2020,2025 and 2032. Population 7000 11000 13500 15500 22500 28500 30200 Year 1940 1950 1955 1960 1970 1985 1990 2000 34540
Construct a sub divided bar diagram
Can you provide any explanation for these results? For THE 3 TABS BELOW: Tab 1, Tab 2 & Tab 3 TAB 1. Year Age of Miss America Murder by steam, hot vapors and hot objects Dev(x) Dev(y) CP 1999 24 7 1.9 2.5 4.69 2000 24 7 1.9 2.5 4.69 2001 24 7 1.9 2.5 4.69 2002 21 3 -1.1 -1.5 1.69 2003 22 4 -0.1 -0.5 0.05 2004 21 3 -1.1 -1.5 1.69 2005 24 8 1.9 3.5 6.60 2006 22 4 -0.1 -0.5 0.05 2007 20 2 -2.1 -2.5 5.32 2008 19 3 -3.1 -1.5 4.78 2009 22 2 -0.1 -2.5 0.23 Mean 22.1 5 Sum 34.45 Standard Deviation 1.75810 2.25227 Covariance 3.45 Correlation Coefficient 0.87013 0.87013 TAB 2 Year Letter in Winning World of Scripps National Spelling Bee Number of people Killed by venomous spider Dev(x) Dev(y) CP 1999 9 6 -1.0 -1.4 1.36 2000 8 5…
Table 1. VITAL STATISTICS OF COUNTRY Y 2020 2018 2015 Total population 109,035,343 100,981,437 92,337,852 Total marriages (Based on civil registration) 240,183 431,972 449,169 Total population of women 15-44 years old 32,962,017 28,625,793 26,417,734 Total Births (Based on civil registration) Male 990,390 750,871 632,870 Female 952,126 972,802 487,798 Total Deaths (Based on civil registration) Timely 506,530 509,762 473,987 Late 106,820 110,382 116,803 Deaths during pregnancy 7,938 7,099 6,759 Fetal deaths Early 1,942 1,236 1,326 Intermediate 1,435 1,161 1,288 Late 1,157 1,311 1,046 Infant deaths Less than 7 days 839 623 795 Less than 28 days 1,961 1,911 1,863 Less than 1 year 3,534 3,658 3,080 Top 3 Leading Causes of Mortality 1. Diseases of the circulatory system 691,225 625,213…
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.
The information is as follows: Month, Cases of Lyme Disease, Drowning Deaths: Month: January, February, March, April, May, June, July, August, September, October, November, December Cases of Lyme Disease: 3, 2, 2, 4, 5, 12, 22, 13, 6, 5, 4, 1 Drowning Deaths: 0, 1, 2, 1, 2, 9, 15, 5, 6, 3, 3, 1, 0 a) Compute the correlation coefficient for the data. b) Is there a significant linear relationship? c) Do you believe an increase in Lyme disease causes an increase in the number of drownings? d) A “lurking variable” is a variable that influences both of the variables (cases of Lyme disease and number of drownings) in a linear correlation study that is unknown or not accounted for in the study. Name one possible lurking variable that might cause the number of Lyme disease cases and drownings to be correlated.
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.