The following model studies the effect that a chemical spill disaster had on nearby housing values. They used data from a sample of houses sold in 1980, before chemical spill disaster happened, and a separate sample ofhouses sold in 1985, after chemical spill had occurred.where the variables used in the analysis are:log(price) is natural log of selling price in $y85 is a dummy variable equal to 1 if a house was sold in 1985, 0 otherwisefar is a dummy variable equal to 1 if a house was far from the affected area, 0 otherwiseIf the chemical spill reduces the value of houses closer to the affected area, which of the following statement is correct?Select one:O a. a₁ is expected to be positiveO b.O c.O d.log(price) = a + Boy85 + a₁ far + B₁y85 * far + ua₁ is expected to be negativeB₁ is expected to be positiveB₁ is expected to be negative

Given regression model is:log(price)=α0+β0y85+α1far+β1y85*far+u, where: log(price) is the natural…

Answered: The following model studies the effect…

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 show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams55606570758085 Vitamin Ccontent in mg11.614.115.918.920.322.825.5 A) Find the regression equation: y= x+Round your answers to 3 decimal placesB) Answer the following questions using your un-rounded regression equation. If we test 115 grams of raspberries what is the expected Vitamin C content? mg(round to the nearest tenth)
Mercury is a persistent and dispersive environmental contaminant found in many ecosystems around the world. When released as an industrial by-product, it often finds its way into aquatic systems where it can have deleterious effects on various avian and aquatic species. The accompanying data on blood mercury concentration (µg/g) for adult females near contaminated rivers in a state was read from a graph in an article. 0.20 0.23 0.24 0.30 0.35 0.41 0.54 0.57 1.43 1.70 1.82 2.20 2.24 3.08 3.24 (a) Determine the values of the sample mean and sample median. Hint: xi = 18.55. (Round your answers to four decimal places.) x== Explain why they are different. The sample mean and sample median are never equal.They aren't different since the data is symmetric. There is heavy negative skewness in the data.There are an odd number of data values.There is heavy positive skewness in the data. (b) Determine the value of the 10% trimmed mean.…
Below, we see a snippet of a dataset that consists of 128 observations and 15 variables. We present two models describing the linear relationship between the BodyFat and other variables. Density BodyFat Age Weight Height Neck Chest Abdomen Hip Thigh Knee Ankle 1 1.0708 12.3 23 154.25 85.2 94.5 59.0 37.3 21.9 2 1.0853 6.1 22 173.25 83.0 98.7 58.7 37.3 3 1.0414 87.9 99.2 59.6 38.9 4 1.0751 86.4 101.2 5 1.0340 100.0 101.9 63.2 42.2 6 1.0502 94.4 107.8 66.0 42.0 23.4 24.0 67.75 36.2 93.1 72.25 38.5 93.6 25.3 22 154.00 66.25 34.0 95.8 10.4 26 184.75 72.25 37.4 101.8 28.7 24 184.25 71.25 34.4 97.3 20.9 24 210.25 74.75 39.0 104.5 60.1 37.3 22.8 24.0 25.6 Biceps Forearm Wrist 1 32.0 27.4 17.1 2 30.5 28.9 18.2 3 28.8 25.2 16.6 32.4 29.4 18.2 5 32.2 27.7 17.7 6 35.7 30.6 18.8 Analysis of Variance Table Model 1: x$BodyFat ~ x$Neck Model 2: x$BodyFat x$Neck + xSWeight + x$Height F Pr (>F) Res. Df RSS Df Sum of Sq 1 250 13348.1 2 248 9461.4 2 3886.7 50.939 < 2.2e-16 *** --- Signif. codes: 0***…
Suppose an oceanographer monitors the daily salinity of a particular ocean in relation to the temperature of the water. The oceanographer plots the data with temperature, in degrees Celsius (°C), along the horizontal axis and salinity, in parts per thousand (ppt), along the vertical axis. Select the true statement about the data point identified by the arrow. An ocean temperature of 21 °C causes the salinity to be 29 ppt. The predicted salinity is 29 ppt when the ocean temperature for the day is 21 °C. An ocean temperature of 29 °C corresponds to a salinity level of 21 ppt. The observed salinity is 29 ppt when the ocean temperature for the day is 21 °C. There is no relationship between the temperature of the ocean on a given day and salinity.
The cost of fuel is the largest component of cost of ownership for most vehicles. Fuel cost is (almost) inversely proportional to gas mileage; higher gas mileage means lower fuel cost and vice-versa. If you keep track of the number of miles driven on each tank of gas as well as how much gas is purchased, it is easy to calculate gas mileage; many cell phone apps exist to track this. The data in the following table is the gas mileage for Mr. Hebert's 2015 Jeep Wrangler Unlimited. 12.85 14.98 15.36 17.09 18.86 13.28 15.11 15.62 17.50 19.07 13.48 15.12 15.65 17.66 20.91 14.65 15.13 16.41 18.17 21.17 14.71 15.14 16.80 18.27 22.11 e. Does this data show any skew or symmetry? A. Left - Skewed B. Right - Skewed C. Symmetrical
Explain in your own words how simple regression can be helpful in identifying relationships between variables.
Researchers often rely on surveys to capture a subjective assessment of well-being. One study finds that holding everything else constant, people seem to be least happy when they are in their 40's. Another study suggests that money does buy happiness, but its effects diminishes as income rises above $75000 a year. The accompanying data file includes survey daa of 100 working adults' self-assessed happiness on a scale of ) to 100, along with their age and annual income. Estimate and interpret a regression model based on Age, Age 2 and income. Predict happiness with income equal = to $80000 and age equal to 30, 45, and 60 Years Predict happiness with Age equal = to 60 and income equal to 25,000, 75000, and 125000 Happiness Age Income 69 49 52000 83 47 123000 86 72 112000 73 52 166000 89 68 90000 81 37 152000 75 48 58000 56 48 50000 75 56 93000 57 51 27000 77 60 173000 83 55 173000 85 75 68000 82 69 157000 63 39 40000 70 66 107000 78 34 109000 53…
You were asked to help with an analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers’ AGE at birth (continuous variable in years), mothers’ current HOUSING status (“own” and “not-own”; “own” is the reference group), and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”; “Manhattan” is the reference group). Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE on BW while adjusting for mother’s current HOUSING status and BOROUGH. If you use dummy or binary variables, specify what they mean. Write down the population model that estimates the effect of mother’s AGE…
Which of the following belongs to lagging indicators A. Manufacturers' new orders B. Stock prices, 500 common stocks C. Average duration of unemployment D. Industrial production
If the relation between Y and X is nonlinear, explain using appropriate mathematical statistics the effect on Y of a change in X.
The cost of fuel is the largest component of cost of ownership for most vehicles. Fuel cost is (almost) inversely proportional to gas mileage; higher gas mileage means lower fuel cost and vice-versa. If you keep track of the number of miles driven on each tank of gas as well as how much gas is purchased, it is easy to calculate gas mileage; many cell phone apps exist to track this. The data in the following table is the gas mileage for Mr. Hebert's 2015 Jeep Wrangler Unlimited. 12.85 14.98 15.36 17.09 18.86 13.28 15.11 15.62 17.50 19.07 13.48 15.12 15.65 17.66 20.91 14.65 15.13 16.41 18.17 21.17 14.71 15.14 16.80 18.27 22.11 a. Find the average fuel economy. x =enter your response here (Round your answer to 3 decimal places.)
The cost of fuel is the largest component of cost of ownership for most vehicles. Fuel cost is (almost) inversely proportional to gas mileage; higher gas mileage means lower fuel cost and vice-versa. If you keep track of the number of miles driven on each tank of gas as well as how much gas is purchased, it is easy to calculate gas mileage; many cell phone apps exist to track this. The data in the following table is the gas mileage for Mr. Hebert's 2015 Jeep Wrangler Unlimited. 12.85 14.98 15.36 17.09 18.86 13.28 15.11 15.62 17.50 19.07 13.48 15.12 15.65 17.66 20.91 14.65 15.13 16.41 18.17 21.17 14.71 15.14 16.80 18.27 22.11 c. Find the five number summary. enter your response here, enter your response here, enter your response here, enter your response here, enter your response here

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