Example 7.12: The following forecasting equation has been derived by aleast-squares method:ŷ =10.27 + 1.65x (Base year:1992; x = years; y = tonnes/year)Rewrite the equation by(a) shifting the origin to 1997.(b) expressing x units in months, retaining yn tonnes/year.(c) expressing x units in months and y in tonnes/month.

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Answered: Example 7.12: The following forecasting…

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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A red maple sapling was 3 feet tall when planted in 2010. Six years later, the tree was 18 feet tall. The growth rate of the tree is constant over time. Find a linear model for the height H (in ft) of the red maple t years after 2010. Let t = 0 represent 2010. H = What is the expected height (in ft) of the red maple in 2020? ft
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1.2. In order to prepare the dataset for modelling, it became clear that RATIO repeats with similar values. The analyst decided to regard them also as categorical variables. Amend the dataset fully in order to build a regression model. Use an ascending order in the coding structure. 1.3. Show the new amended data set and formulate the regression model that must be estimated. Apply all the changes done to the dataset in Question 1.2 and give the regression function. 1.4. The estimated response function is obtained using the coding structure of Question 1.2. Ŷ = 1.34 + 0.034X₁ + 0.049 X₂ -0.041 X3 + 0.029X4 +0.011 X5 +0.08X6. Explain the regression coefficients b₁, b, and b. 1.5. Find the fitted response function for the rotational METHOD of farming on a farm with RATIO of 0.8. 1.6. Refer to Question 1.5. The analyst has a suspicion that there is interaction between the size and the age of the farm if the method of farming is rotational and the field/land ratio is 0.8. Give the response…
Based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and number of views? A popular television show recently released a video preview for the upcoming season on its website. As fans of the show discover the video, the number of views of the preview video has grown each day during the last 2 weeks. The number of days since the release of the video and the natural log of the number of video views is shown in the scatterplot. O An exponential model is appropriate because the residual plot does not show a clear pattern. O A linear model is appropriate because the scatterplot shows a strong, positive linear relationship. In(Views) vs. Days O A power model is appropriate because the scatterplot of days and natural log of views is strong and linear. 10 9.5 An exponential model is appropriate because the relationship between days and the natural log of views is linear, and the residual plot does not show a clear…
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) 860 O 85.8 69.9 1110 765 864 1188 1171 1232 1167 82.9 67.6 70.4 84.5 89 93.9 The regression equation is y =+ (Ox. (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.)
Table #7.3.7 contains pulse rates after running for 1 minute, collected from females who drink alcohol ("Pulse rates before," 2013). The mean pulse rate after running for 1 minute of females who do not drink is 97 beats per minute. Do the data show that the mean pulse rate of females who do drink alcohol is higher than the mean pulse rate of females who do not drink? Test at the 5% level. Table #7.3.7: Pulse Rates of Woman Who Use Alcohol 176 150 150 115 129 160 92 80 60 115 120 125 89 132 120 120 88 74 68 110 68 87 88 72 77 84 67 59 64 117
You are asked to estimate the model wage=B1+B2 EDU+ B3 EDU? where wage is the hourly wage ($) and EDU is the number of years of education. OLS results from a sample of 1000 university graduates are reported below: Wage=9.79-1.20 EDU+0.089 EDU2; R-square%-D0.23 se (2.67) (0.40) (0.09) Test the hypothesis that the expected effect of an extra year of education on hourly wage of an individual with 12 years of education is $1 against the alternative that it is less than $1 at 5% significance level (show all work). You are given the se(b2+2"b3 EDU)=D 0.045 Paragraph BI II
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Suppose you wanted to estimate the effect of being educated on being in the labor force. You estimate a model with two variables, LF is a binary variable = 1 if the person is participating in the labor force and the variable educ measures the number of years of education a person has received. You get the following estimated regression: LF = 0.1 + 0.15educ Which of the following is the correct interpretation about the effect of an additional year of education? O A 1% increase in education increases the number of those participating in the labor force by 15 percentage points. A additional year in education increases the number of those participating in the labor force by 0.15 percentage points A additional year in education increases the number of those participating in the labor force by 0.15% An additional year of education increases the probability of participating in the labor force by 15 percentage points. An additional year of education increases the probability of participating…
A) Compute the last-squares regression line for predicting US emission from NON US - emissions. b) If the non-US emission differ by 0.2 from one year to the next by how much would you predict the US- emission to differ?
The following regression was derived from data collected from 1568 individuals: Yi= 2500i +147Xi – 23 Xi 2 Standard error (165) (46) (7) R 2 = 0.87 F-value is significant at 5% level (a) Given the above equation which depicts the effect of schooling (Xi) on income (Yi) discuss the importance of the quadratic term, Xi 2 (b) Interpret the coefficients in the model (c) Briefly explain how we can investigate whether the model faces the problem of multicollinearity
pan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. An article reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). The following data was read from a graph in the article. x 125.8 98.1 201.4 147.3 145.9 124.7 112.2 120.2 161.2 178.9 159.5 145.8 75.1 151.5 144.2 125.0 198.8 133.9 y 77.9 76.8 81.5 79.8 78.2 78.3 77.5 77.0 80.1 80.2 79.9 79.0 76.9 78.2 79.5 78.1 81.5 71.0 (a) Determine the slope and intercept of the estimated regression line. (Round your answers to 5 decimal places, if needed.)slope: intercept: (b) Does there appear to be a useful linear relationship? Carry out a test using the ANOVA approach and a significance level of 0.05. State the appropriate null and alternative hypotheses.…

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