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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find the linear correlation coefficent and the critical value(s)
Table of critical values shown to the right. Is there sufficient evidence to A data set includes weights of garbage discarded in one week from 62 different hou support the claim that there is a linear correlation between weights of discarded pa Correlation matrix: Variables Paper Glass Click here to view a table of critical values for the correlation coefficient. |Раper 10.3890 Glass 0.3890 1 a = .05 a = 01 4 .950 .990 .878 .959 Determine the null and alternative hypotheses. 6 .811 .917 7 .754 .875 Ho: P 8. .707 .834 9. .666 .798 (Type integers or decimals. Do not round.) 10 .632 .765 11 .602 .735 Identify the test statistic, r. 12 .576 .708 13 .553 .684 r = (Round to three decimal places as needed.) 14 .532 .661 15 .514 .641 Identify the critical value(s). (Round to three decimal places as needed.) 16 .497 .623 17 .482 .606 O A. There is one critical value at r= 18 .468 .590 19 .456 .575 B. There are two critical values at r = ± 20 .444 .561 25 .396 .505 State the conclusion. 30 .361…
1.) Interpret the SPSS output below. (USING THE FIRST PICTURE) 2.) Based on the SPSS correlation matrix below, what do we know about the t-score value for each tested relationship? (USING THE SECOND PICTURE)
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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…
Can you please check my work
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