The table displays data on corn yield (in bushels per acre) and total production (in millions of bushels) in a country for selected years since 1950. Here, \( x \) denotes the number of years since 1900. The goal is to determine a logarithmic regression model (\( y = a + b \ln x \)) for predicting yield and to estimate the yield for the year 2023.### Table Data:- **Year 1950**: \( x = 50 \), Yield = 41- **Year 1960**: \( x = 60 \), Yield = 57- **Year 1970**: \( x = 70 \), Yield = 83- **Year 1980**: \( x = 80 \), Yield = 93- **Year 1990**: \( x = 90 \), Yield = 116- **Year 2000**: \( x = 100 \), Yield = 142- **Year 2010**: \( x = 110 \), Yield = 154### Instructions for Calculations:1. **Complete the Regression Model**: \( y = \left[ \, \right] + \left[ \, \right] \ln x \). Round to one decimal place as needed.2. **Estimate Yield for 2023**: Provide the estimated yield in bushels per acre, rounded to the nearest integer. This activity involves fitting a logarithmic regression equation to the given data, which is a common method used in predicting trends and is especially useful when growth rates are expected to change at a diminishing rate.

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Answered: The table shows the yield (in bushels…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

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Contains data on brain mass in different species versus glia-neuron ratio, the latter being a measurement of brain metabolism as the glia provides the metabolic needs of the neurons. The relationship between THE LOGARITHM of the brain mass (in the third column) and Glia-neuron ratio (fourth column) appears linear and it is these two variables that we wish to analyze via linear regression. We would like to know if the human brain fits the trend from the other species. Towards this end we will perform the regression on all species EXCEPT humans (Homo sapiens). Again, throw out the human data from your analysis. You will however need the human numbers for some of the questions. The analysis to be performed is as follows: 1. Calculate the regression line (slope and intercept) 2. Perform an ANOVA test of the null hypothesis for zero slope. From this analysis, obtain SStotal, SSregression and SSresidual as well as the corresponding MS statistics. 3. Perform a t-test of the null…
The y-intercept in a linear regression model is always relevant and of interest to investigators for every model constructed. True False
Define linear regression?
Biochemical oxygen demand (BOD) measures organic pollutants in water by measuring the amount of oxygen consumed by microorganisms that break down these compounds. BOD is hard to measure accurately. Total organic carbon (TOC) is easy to measure, so it is common to measure TOC and use regression to predict BOD. A typical regression equation for water entering a municipal treatment plant is BOD = -55.47 + 1.505 TOC Both BOD and TOC are measured in milligrams per liter of water. (a) What does the slope of this line say about the relationship between BOD and TOC? TOC rises (falls) by 1.505 mg/l for every 55.47 mg/l increase (decrease) in BOD BOD rises (falls) by 55.47 mg/l for every 1 mg/l increase (decrease) in TOC TOC rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in BOD BOD rises (falls) by 1.505 mg/l for every 1 mg/l increase (decrease) in TOC
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 784 838 822 949 1188 813 Temperature (°F) 65.7 67.8 66.2 79.9 92.3 73.5 What is the regression equation? What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? The best predicted temperature when a bug is chirping at 3000chirps per minute are? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an…
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Annual high temperatures in a certain location have been tracked for several years. Let X represent the number of years after 2000 and Y the high temperature. Based on the data shown below, calculate the linear regression equation using technology (each constant to 2 decimal places). X y 3 35.01 4 37.78 5 37.35 6 36.72 7 40.09 8 40.36 9 40.83 10 41.3 11 40.57 12 42.64 13 44.21 14 42.58 15 46.05 16 45.12 The equation is ĝ ŷ = X + Interpret the slope O For each additional 33.75 years, the annual high temperature will increase by 1 degree on average. O For each additional year, the annual high temperature will increase by 33.75 degrees on average. For each additional year, the annual high temperature will increase by 0.74 degrees on average. O For each additional 0.74 years, the annual high temperature will increase by 1 degree on average. Interpret the y-intercept O In 2000, the temperature was about 33.75. O In 2003, the temperature was about 33.75. O In 2003, the temperature was about…
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The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 760 1119 1125 850 965 785 D Temperature (°F) 70.5 90.8 90.8 74.7 77.1 69.9 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.)
Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has. A. True B. False
Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C
The table shows the yield (in bushels per acre) and the total production (in millions of bushels) for com in a country for selected years since 1950. Let x represent years since 1900. Find a logarithmic regression model (y= a + b In x) for the yield. Estimate the yield in 2020. The regression model is y=+nx. (Round to one decimal place as needed.) The estimated yield in 2020 is bushels/acre. (Round to the nearest integer) Year 1950 1940 1970 1980 1990 2000 2010 *8828889 50 60 70 90 100 110 Yield 37 51 82 98 117 134 153

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