The table below show data that has been collected from different fields from various farms in a certainvalley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content inmg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries.grams5060708090100110Vitamin Ccontent in mg9.314.318.923.527.531.736.9A) Find the regression equation: y =placesx +Round your answers to 3 decimalB) Answer the following questions using your un-rounded regression equation.If we test 140 grams of raspberries what is the expected Vitamin C content?nearest tenth)mg (round to the

Let X gram Y be vitamin c Data given X: 50,60,70,80,90,100,110 Y:…

Answered: The table below show data that has been…

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. 11.8 8.5 7 3.3 2.5 2.8 2.2 0.6 14.2 11.6 10.3 7.1 6.4 6.7 6.2 4.8 thousands of automatic weapons = murders per 100,000 residents This data can be modeled by the linear equation ŷ = 0.84x + 4.33 a. How many murders per 100,000 residents can be expected in a state with 9.1 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residents b. How many murders per 100,000 residents can be expected in a state with 4.3 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residents
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Data were gathered and displayed on the scatter plot. 15 y 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Which of the following is the best equation to model the data? ŷ = 11.5(0.81)* Oŷ = 8.1(0.115)* Oŷ= -0.115x+8.1 Oŷ=-0.81x+11.5
Construct a scatter plot of the data in the table AND create a linear model. 2 10 12 10 14 14 16 18 18 24 a EGO (99- 2.
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.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.6 8.5 7.2 3.6 2.6 2.3 2.1 0.4 yy 13.8 11.4 9.9 7.1 5.9 5.8 5.8 4.7 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.84x+4.02.y=0.84x+4.02. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) 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.B) How many murders per 100,000 residents can be expected in a state with 10.3 thousand automatic weapons?Answer = Round to 3 decimal places.
The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. 11.6 8.1 7.1 3.9 2.9 2.6 2.1 0.7 13.7 10.7 10.2 7 6.5 6.5 5.7 4.7 thousands of automatic weapons y = murders per 100,000 residents This data can be modeled by the linear equation 0.83x + 4.08 a. How many murders per 100,000 residents can be expected in a state with 10.3 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residents b. How many murders per 100,000 residents can be expected in a state with 2.5 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residents
An analyst wanted to analyze the relationship between the speed of a car (x) measured in mph and its gas mileage (y). As an experiment a car is operated at several different speeds and for each speed the gas mileage is measured. These data are shown below. Speed 25 35 45 50 60 65 70 Gas Mileage 40 39 37 33 30 27 25 What is the dependent variable? What is the independent variable?
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $135 million. Use a significance level of alpha equals 0.05 . Budget left parenthesis $ right parenthesis in Millions 45 24 115 74 72 48 117 67 4 60 124 24 6 152 8 Gross left parenthesis $ right parenthesis in Millions 115 10 95 69 127 112 93 101 50 102 223 26 18 282 56 The regression equation is ŷ = __ + __x. (Round to one decimal place as needed.)
Life expectancy in the United States has been rising since the nineteenth century. The table shows the U.S. life expectancy in selected years. Year 1950 1960 1970 1980 1990 2000 Life expectancy at birth 68.2 69.7 70.8 73.7 75.4 77 a. Let t represent the number of years after 1950, and plot the data. Draw a line a best fit for the data points. 80+ 76- 5 10 15 20 25 30 35 40 45 50 Draw: 72+ 64- 60+ 56 52 48- 44 Clear All

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