The questions below can be answered using the tables or the regression equations found in the problem above.The mosquito population in a localpark is changing exponentially.# of daysof mosquitos6505382.4423844.3092506.2201628148The point (10, 101) lies on the graph of the regression equation. What does that point mean for the situation?At this rate, what will be the mosquito population after 2 weeks?People in the United States aredrinking less of a certain juice thanthey have in the past.# years since#of gallons ofjuice "A" per year198010.58.37.010155.7 162148The point (10, 101) lies on the graph of the regression equation. What does that point mean for the situation?At this rate, what will be the mosquito population after 2 weeks?People in the United States aredrinking less of a certain juice thanthey have in the past.# years since# of gallons ofjuice "A" per year198010.558.3107.0155.7204.2253.8302.9Is this exponential growth or decay?Use your regression equation to predict how much of the juice the average person drank in the year 2012. aboutgallons

Note: Hey there! Thank you for the question. As you have posted multiple questions, we have helped…

The questions below can be answered using the tables or the regression equations found in the problem above. The mosquito population in a local park is changing exponentially. of days aof mosquitos 650 53871 442 71 384 309 3. 4. 250 220 7. 162 The point (10,101) lies on the graph of the regression equation. What does that point mean for the situation? At this rate, what will be the mosquito population after 2 weeks?

The questions below can be answered using the tables or the regression equations found in the problem above. The mosquito population in a local park is changing exponentially. of days aof mosquitos 650 53871 442 71 384 309 3. 4. 250 220 7. 162 The point (10,101) lies on the graph of the regression equation. What does that point mean for the situation? At this rate, what will be the mosquito population after 2 weeks?

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

(Medicare). The annual expenditures for Medicare (in billions of dollars) by the US Government for selected years since 1980 are shown in Table 4. Let x represent the years since 1980. (Use 4 decimal places in all answers.) Table 4: Medicare Expenditures Year Billion $ 1980 37 1985 72 1990 111 1995 181 2000 197 2005 330 A. Find the exponential regression model for the data.M(x) = B. What is the r2 value for this model?r2 = C. Extimate (to the nearest billion) the expenditures in 2008?The Medicare expenditures in 2008 were about $ billion.
(d) If the life expectancy is increased by 3.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 84 years. Round to two decimal places.
Illustration 15.37. You are given the following data: y 85 Arithmatic mean 36 S.D. 11 Coefficient of correlation = 0.66. (i) Find the two regression equations. (ii) Estimate the value of x when y = 75.
(please solve within 15 minutes I will give thumbs up)
The local coffee shop keeps track of how much coffee they sell versus the temperature on that day, here are their figures: Sales in Php 1651 1757 1437 1525 1349 1231 Temp in Celsius 21.6 22.6 25 27.3 29.8 30.1 Suppose you want to create a regression equation that will predict the total sales in Php using the temperature of the day in Celcius, what is the total sales for the day in Php if the temperature is 31.5? Round your answers to the nearest hundredths.
Table 3 gives the market value of a luxury sedan (in dollars) xyears after its purchase. Find an exponential regression model of the form y= ab* for this data set. Estimate the purchase price of the sedan. Estimate the value of the sedan 10 years after its purchase. Round answers to the nearest dollar. TABLE 3 Value ($) 1 23,125 19,050 3 15,625 11,875 5 9,450 6 7,125 2.
Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in °F. Find the regression equation, letting chirps in 1 minute be the independent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Chirps in 1 min Temperature (°F) 913 1086 969 1081 1249 1138 1153 850 78.9 82.2 79.6 86.3 92 90.8 88 68.1 C The regression equation is y = + (x. (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.)
The fitted regression is Sales = 842 − 37.5 Price. (a-1) If Price = 1, what is the prediction for Sales? (Round your answer to 1 decimal place.) (b) If Price = 20, what is the prediction for Sales?
. Fill in the "Years since 1970" column for the data to the right. Make a scatter plot in Excel of the data using Years since 1970 and Total Waste in Millions of Tons (Title your graph and label your axes appropriately). How would you best describe the trend? Add an exponential regression model to the data. Write the equation below. Is it a good fit? Explain how you know. Based on the exponential model, what is the growth rate per year? Explain the meaning of the growth rate in the context of the data. Using the exponential model, make a prediction of how much plastic will be in landfills (and the ocean gyres) by Year Years since 1970 Total Waste in Millions of Tons 1970 0 249 1980 10 798 1985 15 1200 1990 20 1740 1995 25 2440 2000 30 3390 2005 35 4600 2010 40 6060 2015 45 7820 Do you think recycling alone will solve this problem (See Q11 and Q12)? What are some of the challenges in recycling plastic that might hinder the world from recycling all plastic…