Which of the following analysis is the most appropriate for the data shown below?1.00-Extinction probability0.75 -0.500.25-0.00-O CorrelationO Logistic RegressionO Nonlinear RegressionO ANCOVAHomeO Regression100•000200Connectivity300●

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Answered: Which of the following analysis is 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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Simple linear regression results: Dependent Variable: Heart. DiseaseIndependent Variable: BikingHeart. Disease = 18.115809 - 0.20845321 BikingSample size: 68R (correlation coefficient) = -0.94616452R-sq = 0.8952273Estimate of error standard deviation: 1.5273175 Correlation between Biking and Heart. Disease is: -0.94616452. Correlation between Smoking and Heart. Disease is: 0.32421. 1) State r 2 (i.e., the coefficient of determination) for “Biking” and “Heart.Disease” and explain what this value means in context of the data set.
Chapter 9, Section 2, Exercise 030 Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 304.5 304.5 2.01 0.158 Residual Error 174 26361.0 151.5 Total 175 26665.5 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=
What does the correlation matrix for a multiple regression analysis contain?A. Multiple correlation coefficientsB. Simple correlation coefficientsC. Multiple coefficients of determinationD. Multiple standard errors of estimate
(b) Compute the linear correlation coefficient between MRI count and IQ. Are MRI count and IQ linearly related? Select the correct choice below and, if necessary, fill in the answer box to complete your choice. (Round to three decimal places as needed.) critical values table 3 0.997 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 n
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The table below lists weights (carats) and prices (dollars) of randomly selected diamonds. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence o support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with a diamond that weighs 0.8 carats. Weight Price 0.3 $508 a. Find the explained variation. 0.4 $1153 0.5 $1332 Round to the nearest whole number as needed.) . Find the unexplained variation. Round to the nearest whole number as needed.) c. Find the indicated prediction interval.
Which of the following tools is not appropriate for studying the relationship between two numerica variables? Correlation coefficient Scatter plot Historam Regression
The following regression is fitted using variables identified that could be related to student requestedloan amount, LOAN-AMT($) for returning students of a certain University. ????−??? = ? + ? ?????? + ? ???? + ? ????Where ACCEPT = the percentage of applicants that was accepted by the university, PREV = previous loan amount and OUTS =outstanding loan amountThe data was processed using MNITAB and the following is an extract of the output obtained:EXHIBIT 2Predictor Coef StDev T PConstant -26780 6115 * 0.000ACCEPT 116.00 37.17 3.14 0.003PREV -4.21 14.12 -0.30 **OUTS 70.85 15.77 4.49 0.000S = 2685 R-Sq = 69.6% R-Sq(adj) = 67.7%Analysis of VarianceSource DF SS MS F PRegression 3 808139371 269379790 37.37 0.00Residual Error 49 353193051 7208021Total 52 1161332421a)What is dependent and independent variables? b)Fully write out the regression equation c)What is the sample size used in this investigation? d)Fill in the blanks identified by ‘*’ and ‘**’. e)Is β significant, at the 5% level of…
The fish in my pond have mean length 10 inches and mean weight 4 pounds. The correlation coefficient of length and weight is .9. If the length of a particular randomly selected fish is reported to be 10 inches, then what should we predict for the weight of that fish using simple linear regression? 4 10 2.5 NOT ENOUGH INFORMATION GIVEN NONE OF THE OTHERS
When there are omitted variables in your regression, then... Group of answer choices This has no effect on the estimation of the explanatory variable because the variable is omitted This will always bias the OLS estimation of the explanatory variable the estimation of the explanatory variable(s) is unaffected The OLS estimation is biased if the omitted variables are correlated with the included variable
6
Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…

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Which of the following analysis is the most appropriate for the data shown below? 1.00- Extinction probability 0.75 - 0.50 0.25- 0.00- O Correlation O Logistic Regression O Nonlinear Regression O ANCOVA Home • O Regression 100 200 Connectivity 300 8