7. The cotton aphid poses a threat to cotton cropsin Iraq. The accompanying data ony = infestation rate (aphids/100 leaves)X1 = mean temperature (°C)x, = mean relative humidityappeared in the article “Estimation of the EconomicThreshold of Infestation for Cotton Aphid" (MesopotamiaJournal of Agriculture [1982]: 71–75). Use the data to findthe estimated regression equation and assess the utility ofthe multiple regression modely = a + Bjx1 + Bx2 + eyX1X2yX1X26121.057.07724.848.08728.341.59326.056.09827.558.010027.131.010426.836.511829.041.010228.340.07434.025.06330.534.04328.313.02730.837.01931.019.01433.620.02331.817.03031.321.02533.518.56733.024.54034.516.034.36.02134.326.01833.021.02326.526.04232.028.05627.324.56027.839.05925.829.08225.041.08918.553.57726.051.010219.048.010818.070.09716.379.5Given: significance level = 0.05Required:1. Regression Equation2. F and P-value3. Decision and Conclusion

Answered: Image /qna-images/answer/31c7e4aa-2dd1-4ac7-9523-0f5f2807fdbe.jpg

Answered: The cotton aphid poses a threat to…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

Show the best fitted line on scatter diagram and Find the predicted value for each y using the exposure time and the equation obtained in part b (b. Find the equation of regression line between radiation doses on exposure time .usingleast square method)
Would I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?
4b) The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression equation, using the first variable x (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure (y) reading of 140. What is the correlation coefficient, r? Using a significance level of a = 0.05, is there a significant linear relationship between systolic and diastolic blood pressure? Blood Pressure: Systolic Diastolic 112 125 115 136 143 116 123 124 elimii 70 89 65 90 97 64 SUTT nisinoo aqdM 21.SS bns aqdM 78 ahoqnis erit te zbesqz steb ils to 69 bns ago 20.EI to adimil srit terit sonabilnos 2 nistnoo aqdM 21.SS bnc agdM sgsavs arit ferli mislo a hoqnis orti roqque lovedni sonsbilnos 3028 wolsd insmsisiz tomo artezorio SeqdM 2.55 al 2.SS to sulavadi znistmoodi ezusaed mish ads toqque ton zaob 2.55 to sulsy sdt anistroo ti sausosd mislo ert hoqquz 200b to sulav orit nisinoo ton zoob 11 saussed misbb adi…
A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x₁ = distance traveled (miles) and x₂ = the number of deliveries made. Suppose that the model equation is Y = -0.800+ 0.060x₁ +0.900x₂ + e (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret ₁ = 0.060, the coefficient of the predictor x₁? O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a one-mile (i.e.…
A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x, = distance traveled (miles) and x, = the number of deliveries made. Suppose that the model equation is Y = -0.800 + 0.060x, + 0.900x2 + € (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? 5.8 v hr (b) How would you interpret ß1 = 0.060, the coefficient of the predictor X1? o When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a…
Is the regression equation for predicting Y in terms of X the same as the regression line for predicting X in terms of Y?
If an estimated regression line has a y-intercept of 10 and a slope of -4, then when x= 2, the predicted value of y is?
Interpret the least squares regression line of this data set. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The correct least squares regression line for the data set is: y = 8.116x + 273.273 Use it to complete the following sentence: The least squares regression line predicts an additional annual rainfall if the average temperature of coastal waters increases by one degree millimetres of Celsius.
Nine data points of data yield r=0.867 and the regression equation y=19.4+0.93x. Also, y=64.7. What is the best predicted value of y for x=40?
10) A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
This table reports the regression coefficients when the returns of the size-institutionalownership portfolio (columns 1 and 2) returns are regressed on three variables: a constant(column 3), the stock market returns (column 4), and the change of the value weighted discountof the closed end fund industry (column 6). Columns 5 and 7 report the corresponding t-statistics of the coefficient estimates. Note that a t-statistic with an absolute value above 1.96means the coefficient estimate is significantly different from 0 at the 1% level. Column 8reports the R square of the regressions. Column 9 reports the mean institutional ownership ofeach portfolio. The last column reports the F-statistics for a multivariate test of the null hypothesis that the coefficient on ΔVWD in the Low (L) ownership portfolio is equal to theHigh (H) ownership portfolio. Two-tailed p-values are in parentheses. 1. What is the main finding of this Table? 2. What is the explanation for…
A startup team is interested in creating a productivity app. In estimating the cost of creating the app, they collected sample data and developed the following regression equation: where 1 = number of developers b₂ a. What is the value of b2 in the equation? 2= number of hours spent creating the app Is cost of software and testing ($'000) y = total cost of creating app ($'000) b. Does it make sense to interpret by in this equation? OYes y = -8.825+20.4861 +0.56x2 + 1.02x3 O No $ c. Predict the cost of creating an app involving 3 developers, 650 hours and $18,000 in software and testing costs. Accessibility Investigate 8

SEE MORE QUESTIONS

Recommended textbooks for you

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

SEE MORE TEXTBOOKS