KThe accompanying data represent the yearly amount of solar power installed (in megawatts) in a particular area from 2000 through 2008. The trend forecasting equations below were found, where X is the number of years after 2000. Complete parts (a) through (d) below.Y = -9.156+28.5667X, Y₁ = 22 46 +1.467X₁ +3.3874X²Click the icon to view the data table.a. Compute the standard error of the estimate (Syx) for each model.LinearQuadraticSyx(Round to three decimal places as needed.)b. Compute the MAD for each model.LinearQuadraticMAD0(Round to three decimal places as needed.).c. On the basis of (a) and (b) and the principle of parsimony, which forecasting model would you select?The model with thevalues of Syx and MAD should be used, which is thequadraticlinearmodel.autoregressive4exponentialYearly Amount of Solar Power InstalledYear200020012002200320042005200620072008Amount(megawatts)162844718598142209253PrintDDoneXClear allCheck answer803:21 PM01/28/2024

Given is the data on number of solar powers installed.We will use R software for calculations.

Answered: The accompanying data represent the…

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 sales manager of a real estate company collected information about the annual sales of his sales agents and their years of experience in selling. Salesperson A B C D E F G Years of experience 1 1 3 4 4 5 6 Annual sales (in thousand pesos) 50 30 80 100 90 120 135 a. Using any statistical software, produce a scatter diagram for these data with years of experience as the independent variable and annual sales as the dependent variable. b. Describe the form, trend, and strength of their association.
The following chart shows the percentage of the U.S. discretionary budget allocated to education from 2003 to 2009 (t = 3 represents the start of 2003). A bar graph titled "Percentage of U.S. budget on education" has a horizontal t-axis labeled "Year since 2000" and a vertical axis labeled "Percentage". The bar graph has 7 bars. Each bar is associated with a label and an approximate value as listed below. 3: 6.8% 4: 7% 5: 7% 6: 6.9% 7: 6.5% 8: 6.3% 9: 6.2% The following table shows the percentage of the U.S. discretionary budget allocated to education in 2003, 2005, and 2009 (t = 3 represents the start of 2003). Year t 3 5 9 Percentage 6.8 7 6.2 Find a quadratic model for these three years. (Round your coefficients to two decimal places.) p(t) = Use your model to estimate the percentage of the U.S. discretionary budget allocated to education in 2007. (Round your answer to two decimal places.)
The table shows data collected on the relationship between the average daily temperature and time spent watching television. The line of best fit for the data is yˆ=−0.66x+88.5. Assume the line of best fit is significant and there is a strong linear relationship between the variables. Temperature (Degrees) Minutes Watching Television 35 66 45 58 55 52 65 46 (a) According to the line of best fit, what would be the predicted number of minutes spent watching television for an average daily temperature of 46 degrees? Round your answer to two decimal places, as needed. Provide your answer below: The predicted number of minutes spent watching television is .
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
A random sample of 136 adults were asked to report the number of hours per week the spent on a computer and their number of years of education. The linear model equation below describes the relationship between the mean computers hours and years of education. computers == 9.12 ++ 0.8 ×× education Based on this linear model, which of the following statements is correct? a) An adult who has no years of education is expected to spend 9.12 hours per week on a computer. b) An adult who has 1 more year of education than another is expected to spend 9.12 more hours per week on a computer. c) An adult who spends 1 more hour per week on a computer than another is expected to have had 9.12 more years of education. d) An adult who spend zero hours per week on a computer is expected to have 9.12 years of education.
A biologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? d) Suppose the correlation coefficient was −0.12. How would you classify the correlation between temperature and amount of glucose?
Use the example of temperature and the amount of ice cream sold in a city each day, we are interested in creating an equation that will allow us to predict the amount of ice cream that are sold in the future simply by knowing temperature. (Please fill out the red blanks with appropriate numbers randomly.) a. Construct a scatter plot of the data. What should the independent variable be? Why? b. Find the values and discuss what the following mean in context.i. The slope of the regression equationii. The y-intercept of the regression equationiii. The correlation riv. The coefficient of determination r2. c. Do the data provide convincing evidence that there is a linear relationship between temperature and the amount of ice cream Carry out an appropriate test at a significance level of 0.05 to help answer this question.
A trendline is given to depict enrollment at a local college where x is the year and y represents enrollment. Y=178.09x-353194 Use the rrendline ro estimate the enrollment for 2009. Round to the nearest whole number.
A researcher explored the relationship between the percent of snow days during the month of January and the percent of students that receive an A on class finals at the same schools. The researcher collects information from 6 schools, shown in the table below. Use the graph below to plot the points and develop a linear relationship between the percent of January snow days and the percent of 'A' final exams. School Number % of Snow Days % of A Finals 1 5 25 2 7 45 3 10 50 4 12 65 5 20 70 6 25 86 Using the linear relationship graphed above, estimate the percent of 'A' finals if there are 2% snow days. Provide your answer below:

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