A new type of corn seed has been developed and a team of agronomistswanted to determine whether there was a significant difference between thetypes of soils that they are planted in (loam, sandy, salty, clay) based on the yieldof the crop, the amount of water required, and the amount of herbicide needed.Eight fields of each type were chosen for the analysis.Correlation matrixyieldwaterherbicideBox's M Testdf1df2Fp-valueyield water herbicide1 0.2026630.202663-0.12991 0.22369414.97038182770.4540.6653920.8479741-0.1299147110.223694166MANOVA1Pillai TraceWilk's LambdaHotelling TraceDeterminant EDetrminant Tstat0.53450.9946916097489.21871826093Group MeansloamsandysaltyclaytotalFyieldwater herbicide69.7125 32.7375 6.387562.57528.24.3555.3125 30.6375 3.862558.8375 33.0875 4.087561.60938 31.16563 4.671875df1df2countBased on the MANOVA output, what is the value of the Wilk's Lambdastatistic? (final answer to 4 decimal places)p-valueeto-sq0.046408 0.1781670.020472 0.2544260.008399 0.24399388What is the value of df1 associated with the F-statistic of Wilk's Lambda? (finalanswer is a whole number)

Given Information: Consider the given Excel output.

Answered: A new type of corn seed has been…

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 researcher wants to make an equation that will predict a person's support for domestic surveillance from a variety of demographic characteristics (e.g., age, income). What method will they use? A) Multiple regression B) Correlation C) Two-factor ANOVA D) One-sample t-test
The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 27 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 27 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. Minitab output The linear correlation coefficient is. (Round to three decimal places as needed.) The regression equation is Highway = 50.4- 0.00535 Weight %3D Predictor Сoef SE Coef T Constant 50.383 2.732 17.75 0.000 Weight - 0.0053502 0.0007856 -7.55 0.000 S= 2.17876 R-Sq = 65.1% R-…
what are the critical values r =?
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 31 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? Yes O No Minitab output The regression equation is Highway = 50.8 -0.00508 Weight Predictor Coef SE Coef T P Constant 50.772 2.793…
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 26 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 3000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 26 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Minitab output The regression equation is Highway = 50.3 -0.00539 Weight Predictor Coef SE Coef Constant 50.288 2.998 Weight -0.0053868 0.0007773 |S=2.11773 R-Sq=64.0% R-Sq(adj) = 60.9% Predicted Values…
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Dataset for question (4.2.) Amount of Money Spent on Vehicle extras by 7 customers: Customer Amount_Spent х1 2300 x2 2386 x3 1920 х4 1578 x5 3065 х6 2312 x7 1790 4.2. A car dealer wants to know if the purchasing habits of buyers buying extras for their vehicles have changed. He is particularly interested in determining if male buyers are willing to spend more money on extras for their cars. Based on data collected over the past year, he has estimated that the distribution of the amount of money spent on extras is approximately normally distributed with an average of R2 000 per customer. To test this hypothesis, he has collected the following information concerning the amount of money that the last seven male customers have spent on extras (Rands). Provide all the steps.
6
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