Concept explainers
GDP Use the following information to answer Exercises 47–50. The gross domestic product (GDP; in tens of trillions of U.S. dollars) for China and the United States can be approximated as follows:
where
Find the projected GDP in 2015 and 2025 for China.
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- US Death Rates Due to Heart Disease (t) years (R) Death Rate (Number of Deaths per 100,000) Years death rate 1960 559 1970 493 1980 412 1990 322 2000 258 Heart Disease Rates The death rate from heart disease in the US for various years is shown in the table. Let R be the death rate (number of deaths per 100,000) from heart disease for the years since 1960 a. Create a scatterplot (in the space above) of the data on the given axes. Draw a line that comes close to the points in your scatterplot. b. Perform a linear regression to find the prediction equation. (be sure to use ) Draw that line on your graph. c. What is the correlation coefficient value? Briefly describe what that value means. d. Using your model, approximate the death rate for the year 1980. e. Find the residual (actual – predicted) for the year 1980.arrow_forward(Source: U.S. Energy Information Administration) T 66-71. Estimating error Refer to Theorem 8.1 in the following exercises.arrow_forwardShow workarrow_forward
- World Population The low long-range world population numbers and projections for the years 1995–2150 are given by the equation y = -0.00036x2+0.0385x + 5.823, where x is the number of yearsafter 1990 and y is in billions. During what yearsdoes this model estimate the population to be above6 billion?arrow_forwardA tank is discharging water through an orifice at a depth x (m) below the surface of water whose area A (m²). The following are the values of the (corresponding values of (A) w.r.t (x : x (m) 1.5 1.65 1.8 1.95 2.10 225 24 255 27 2.85 3 A (m) 125 139 1.52 1.65 181 1.96 212 229 246 2.65 2.83 :Using the following formula 3.0 A dx T = 1.5 Calculate (T) for the level of water to drop from 1.5 m to 3 m by .Simpson's 1/3 rulearrow_forwardt the Blood Bank, they know that O+ blood is the most common blood type and that 40%40% of the people are known to have O+ blood. Blood type A- is a very scarce blood type and only 6%6% of the people have A- blood. Half of the people have blood type A or B. Let: X=X= number of people who have blood type O+ Y=Y= number of people who have blood type A- Z=Z= number of people who have blood type A or Barrow_forward
- t the Blood Bank, they know that O+ blood is the most common blood type and that 40%40% of the people are known to have O+ blood. Blood type A- is a very scarce blood type and only 6%6% of the people have A- blood. Half of the people have blood type A or B. Let: X=X= number of people who have blood type O+ Y=Y= number of people who have blood type A- Z=Z= number of people who have blood type A or Barrow_forwardt the Blood Bank, they know that O+ blood is the most common blood type and that 40%40% of the people are known to have O+ blood. Blood type A- is a very scarce blood type and only 6%6% of the people have A- blood. Half of the people have blood type A or B. Let: X=X= number of people who have blood type O+ Y=Y= number of people who have blood type A- Z=Z= number of people who have blood type A or B Consider a random sample of n=44 people who donated blood over the past three months. Use the relevant probability function of YY to calculate the probability that 44 people in the random sample will have type A- blood.arrow_forwardb. Are there any critical values for either graph? Where are the intersections between the two? What do these intersections represent? c. Find the points where the hours of daylight are at a maximum/minimum. Around what time of the year are these points? Compare the information. d. What tools did you use to solve this problem? What other ways could you have come to find the same solution? e. How many hours of daylight are in each location at t=5? at t=8?arrow_forward
- Find leng th of the Cardioid V-ag from e -oto0 - 1 %3Darrow_forwardLet Xvuniform(0,8) then E(x-2) 4 8 2 3arrow_forwardTo investigate the dependence of energy expenditure on body build, researchers used underwater weighing techniques to determine the fat-free body mass (x) for a group of 7 men. They also measured the total energy expenditure (y) for each man during the conditions of quiet sedentary activity. The results are shown in the table. Fat-Free Mass (kg) Energy Expenditure (kcal) 49.3 1894 59.3 68.3 2050 2353 47.1 1838 57.6 1948 78.1 2528 76.1 2568 Mean 62.257 2168.429 Standard deviation 12.296 308.254 T = 0.97985 a. State the linear regression equation and predict the energy expenditure of a man with 60 kg of fat-free mass, with a significance level of 0.01. Assume the pairs of data follow a bivariate normal distribution and that the scatterplot shows no evidence of a nón-linear relationship in the data. b. Determine the percentage of energy expenditure that is explained by the linear relationship between fat-free mass and energy expenditure.arrow_forward
- Trigonometry (MindTap Course List)TrigonometryISBN:9781337278461Author:Ron LarsonPublisher:Cengage LearningAlgebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage