A firm purchases two types of industrial chemicals. Type I chemical costs $3 per gallon,whereas type II costs $5 per gallon. The mean and variance for the number of gallons of typeI chemical purchased, Y,, are 40 and 4, respectively. The amount of type II chemicalpurchased, Y2, has E(Y2) = 65 gallons and V(Y2) = 8. Assume that Y, and Y2 are independentand find the mean and variance of the total amount of money spent per week on the twochemicals.

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Answered: A firm purchases two types of…

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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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. I 11.9 8.3 7.1 3.5 2.4 2.8 2.2 0.4 Y 14.4 11.2 10.3 7.2 6.1 6.2 6.1 4.7 I thousands of automatic weapons y = murders per 100,000 residents This data can be modeled by the equation ŷ = 0.86x + 4.14. Use this equation to answer the following. A) How many murders per 100,000 residents can be expected in a state with 4.1 thousand automatic weapons? Answer = B) How many murders per 100,000 residents can be expected in a state with 10.7 thousand automatic weapons? Answer Round to 3 decimal places. = Round to 3 decimal places.
3. The police department is assessing its staffing requirements. The department expects that the number of serious crimes committed, C, on average each week is proportional to the number of officers, P, on special street patrol. Data for the past year has been collected and some of it is shown below: P 4 7 9 11 15 17 с 14 11 10 9 7 5 a) Neatly sketch a scatter plot of the data on graph provided below. Which variable is the independent variable that should be plotted on the horizontal axis? Notice that the data seem to fall in a linear pattern. Draw the best-fit line through the data. Label your axes, indicate the scale, and title your graph. Why has only the first quadrant been provided for the graph? b) Look at your best-fit line and identify two good coordinate points that sit right on this best-fit line:
Risky Drivers The following table gives the policereported crashes per million miles traveled for differentage groups.a. Create a scatter plot of the data, with x equal tothe age of the drivers and y equal to the number ofcrashes per million miles travel.b. Find the quartic function that is the best fit for thedata, where x is the age of the drivers and y equalsthe number of crashes per million miles traveled.Report the model with four significant digits.c. Graph the function and the data on the same set ofaxes, for x = 15 to x = 85.d. At what ages is the number of crashes less than 3,according to the model?
Can a low barometer reading be used to predict maximum wind speed of an approaching tropical cyclone? For a random sample of tropical cyclones, let x be the lowest pressure (in millibars) as a cyclone approaches, and let y be the maximum wind speed (in miles per hour) of the cyclone. x 1004 975 992 935 989 928 y 40 100 65 145 80 147 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. (b) Would you say the correlation is low, moderate, or strong? low moderate strong Would you say the correlation is positive or negative? positive negative (c) Use a calculator to verify that x = 5823, x2 = 5,656,235, y = 577, y2 = 64,859 and xy = 553,251 Compute r. (Round your answer to four decimal places.) As x increases, does the value of r imply that y should tend to increase or decrease? Explain your answer. Given our value of r, y…
We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of sixteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Also given is the product of the distance from the beach and the house price for each of the sixteen houses. (These products, written in the column labelled "xy", may aid in calculations.) Distance from the beach, x (in miles) 7.7 18.5 6.3 11.9 11.0 14.6 11.3 3.0 Selling price, y (in thousands of dollars) 290.8 215.0 304.4 269.9 283.2 203.4 212.4 263.2 197.3 272.2 215.1 241.6 312.3 221.5 279.1 236.1 10.9 4.9 12.5 5.8 3.6 5.7 9.4 8.1 Send data to calculator xy 2239.16 3977.5 1917.72 3211.81 3115.2 2969.64 2400.12 789.6 2150.57 1333.78 2688.75 1401.28 1124.28 1262.55…
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.05. Weight, x Variability in braking distance, y 5980 5370 6500 5100 5820 4800 1.72 1.97 1.87 1.63 1.64 1.50 Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: Ha: P Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is. B. The critical values are - to and to %3D Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? There enough evidence at the 5% level of significance to conclude that there a significant linear correlation between vehicle weight and…
We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of fifteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Also given is the product of the distance from the beach and the house price for each of the fifteen houses. (These products, written in the column labelled "xy", may aid in calculations.) Distance from the beach, x (in miles) Selling price, y (in thousands of dollars) xy 5.0 270.1 1350.5 11.5 205.9 2367.85 5.9 309.4 1825.46 12.2 200.6 2447.32 2.6 307.1 798.46 5.9 266.0 1569.4 8.3 297.3 2467.59 18.3 224.2 4102.86 6.5 242.4 1575.6 12.1 192.6 2330.46 11.6 229.4 2661.04 9.5 230.9 2193.55 10.1 277.0 2797.7 13.5 270.8 3655.8 6.2…
The amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). C (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? A. The variable "weekly time spent watching television" is likely skewed right, not normally distributed. OB. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. O C. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. O D. The variable "weekly time spent watching television" is likely normally distributed. O E. The variable "weekly time spent watching television" likely uniform, not normally distributed. (b) According to a certain survey, adults spend 2.45 hours per day watching television on a weekday. Assume that the standard deviation for "time…
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The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.4 7.2 3.6 2.7 2.7 2.2 0.7 yy 13.8 11.5 10 7.2 6.4 6.1 6.2 4.4 xx = thousands of automatic weaponsyy = murders per 100,000 residents This data can be modeled by the equation y=0.84x+4.06.y=0.84x+4.06. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.9 thousand automatic weapons?Answer = Round to 3 decimal places.
A traffic safety company publishes reports about motorcycle fatalities and helmet use. In the first accompanying data table, the distribution shows the proportion of fatalities by location of injury for motorcycle accidents. The second data table shows the location of injury and fatalities for 2061 riders not wearing a helmet. Complete parts (a) and (b) below. Click the icon to view the tables. (a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use α = 0.05 level of significance. What are the null and alternative hypotheses? O A. Ho: The distribution of fatal injuries for riders not wearing a helmet follows the same distribution for all other riders. H₁: The distribution of fatal injuries for riders not wearing a helmet does not follow the same distribution for all other riders. B. Ho: The distribution of fatal injuries for riders not wearing a helmet does not follow the same distribution for all other riders. H₁: The…
1945 is paired with cancer rates for 1975. The cigarette consumption data is from 1945 to 1975 in 5-year increments. There is a strong positive linear association between annual cigarette consumption and lung cancer rates. The correlation is 0.81. If we use the line to make predictions of the number of lung cancer deaths per 100,000 people, which of the following is an example of extrapolation? a. Predict Y when cigarette consumption is 3,500 cigarettes per person. b. Predict Y when cigarette consumption is 3,800 cigarettes per person. c. Predict Y when cigarette consumption is 4,600 cigarettes per person.

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