The following correlation matrix containssimple correlation coefficients between pairsof variables using base year data. Discuss thepossible question of which explanatoryvariables X should be included in linearmultiple regression model.2. The following correlation matrix contains simple correlation coefficients betweenpairs of variables using base year data. Discuss the possible question of whichexplanatory variables X should be included in linear multiple regression model.YXIX20.32X3X4Y1.000.320.950.95X11.000.250.190.03X21.000.990.33X31.000.55X41.00

Given the correlation matrix contains simple correlation coefficients between pairs of variables…

Answered: The following correlation matrix…

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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In a dataset, X is the independent variable, and Y is the dependent variable. Which of the following statement is correct? None of these Regression between X and Y determines the nature of the relationship between the variables. Regression between X and Y determines whether there exists any relationship between the variables. Correlation between X and Y determines the nature of the relationship between the variables.
This is only one question
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
Consider a panel data set and the following regression model. Yit Bo + B₁Xit + ++ Uit What do subscripts / and t refer to? O A. Subscripts i and tidentify different time periods. O B. Subscripts / and t identify the entity and time period respectively. OC. Subscripts i and t identify different individuals. O D. Subscripts i and t identify the time period and entity respectively.
The following table shows the starting salary and profile of a sample of 10 2 p employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of…
Which statement is not correct for multiple regression model? When we interpret this categorical variable, we would say the change we observe when one switches from the reference category to the specific category. The reference category will not be displayed in our model results. If we include a categorical variable with more than two values (e.g., religion) as an independent variable, we want to include a dummy variable for all categories except for two. We can include more than two categorical variables in the model. The value of the independent variable not included in the model is called "reference category."
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
The following data has mid term marks and end term marks of 9 students. Maximum marksfor both mid term marks as well as end term marks is 100. Calculate regression line betweenmid term marks (independent) and end term marks (Dependent) using below dataset. Givedetailed explanation with solution.Student Roll No. 1 2 3 4 5 6 7 8 9Mid TermMarks 67 59 73 63 89 78 64 28 89End TermMarks 55 42 80 83 76 67 63 33 58
There is a dataset of size n = 51 and is for the 50 states and the District of Columbia in the United States. The dependent variable is year 2002 birth rate per 1000 females 18 to 19 years old and independent variable is the violent crime rate (per 1000 population). A simple linear regression model is run with the results given below. What is the Pearson correlation coefficient between x and y variables? The R squared of the model? What kind of relationship there is?
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)
randomly selected middle school students. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 1.5 2 3 3.5 4 4.5 5.5 Overall Grades 99 96 84 75 68 65 60 Table Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.

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