Q1.Consider the following data:46Find out the following:(i)(ii)yKarl Pearson correlation coefficient (r)Regression equation (ŷ)4XAssignment No. 1y55Q2. Calculate Coefficient of determination (R²) from the following data:3457656446Q3. Calculate Estimated Standard error (SE) from the following data:342342Marks in Statistics2455Marks in Mathematics 35 46 45 3032 25 24 163Q4. Calculate the Spearman's rank correlation(r.). from the following data:Q5. Write a short note on Correlation and Regression analysis.6101620 60 2055 20 365 27 10 12 21

Given that X Y 4 6 6 4 5 5 2 4 3 6 NOTE:- According to bartleby guidelines expert…

Answered: Q1. Consider the following data: 4 6 6…

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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If a sample of 25 pairs of data yields a correlation coefficient, r, of 0.390 and the scatterplot displays a linear trend, can you use the regression equation to make predictions, assuming your x-values are within the domain of the data set? Choose your answer from the multiple choice answers below A.) Yes, because rcrit = 0.396 and the regression coefficient, r, is less than this value. B.) Yes, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. C.) No, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. D.) No, because rcrit = 0.396 and the regression coefficient, r, is less than this value.
4.For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 33.88, Σγ^2 = 57365692 (b)Find the fitted regression line of the price of laptop on processor speed. (c) Find the predicted price of the laptop (y) for the processor speed x-1.9. (d) Compute the coefficient of determination and comment.
A sample of n = 15 pairs of X and Y scores produces a Pearson correlation of r = 0.45, SSY = 90. a) If the regression equation was found for these scores, how much of the Y variability would be predicted by the regression equation (SSregression) and how much would not be predicted (SSresidual)? b) Does the regression equation predict a significant portion of the variability for the Y scores? (Equivalently, is the Pearson correlation significant?)
The data is given as follow. xi 2 6 9 13 20 yi 7 18 9 26 23 The estimated regression equation for these data is = 7.6 + .9x.Compute SSE, SST, and SSR (to 1 decimal). SSE SST SSR What percentage of the total sum of squares can be accounted for by the estimated regression equation (to 1 decimal)? %What is the value of the sample correlation coefficient (to 3 decimals)?
4. For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 3388, Σγ^2 = 57365692 a) compute correlation coefficient (b) Find the fitted regression line of the price of laptop on processor speed.
The grades of a class of 9 students on a midterm report (x) and on the final examination (y) are as follows: Give the following: a. linear regression line and equation b. computation of the coefficient of determination ?^2 c. Computation of the coefficient of correlation ? d. Estimate the final examination grade of a student who received a grade of 85 on the midterm report.
The following data shows the dexterity test scores of five assembly-line employees of Dimples Company Limited and their respective hourly productivity.Employee Score on dexterity test (?) Ali 12Kofi 14Kwesi 17Abudu 16Nana 11Units produced in an hour (?) 55636770 51You are required to(i) Write the regression equation(ii) Interpret the regression equation(iii) Calculate the Pearson’s Product Moment Correlation Coefficient.(iv) Interpret the correlation coefficient (v) Suppose the dexterity test score is 13, what would be the units produced in an hour? (vi) Clearly explain (in detail) the difference between regression analysis and correlation analysis.
Consider the following regression equation specied for 2-period panel data: where i = 1; 2; :::N and t = 1; 2. If you expect that β_1 is positive, but the correlation between Δx_i and Δu_i is negative, thenwhat is the bias in the OLS estimator of β_1 in the first-differenced equation?
Ten observations were provided for a dependent variable y and two independent variables x1 and x2; for these data, SST = 15,189.8 and SSR = 14,056.9. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (c) Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) , after adjusting for the number of independent variables in the model, we see that % of the variability in y has been accounted for.
Given that the means of x and y are 64 and 66 , their standard deviations are 2.8 and 3.2 respectively and the coefficient of correlation between them is 0.5. 1) write down the regression lines.
Ten observations were provided for a dependent variable y and two independent variables x1 and x2; for these data, SST = 15,177.6 and SSR = 14,056.5. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b)Compute Ra2.( Round your answer to three decimal places.) Ra2 = (c)Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) (Select Yes OR No) after adjusting for the number of independent variables in the model, we see that ______% of the variability in y has been accounted for.
2. The following data, adapted from Montgomery, Peck, and Vining (2001), present the number of certified mental defectives per 10,000 of estimated population in the United Kingdom ( y) and the number of radio receiver licenses issued (x) by the BBC (in millions) for the years 1924 through 1937. Fit a regression model relating y and x. Comment on the model. Specifically, does the existence of a strong correlation imply a cause-and-effect relationship?

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Q1. Consider the following data: 4 6 6 4 Assignment 5 5 2 4 3 6 Find out the following: (i) Karl Pearson correlation coefficient (r) (ii) Regression equation (9) Q2. Calculate Coefficient of determination (R²) from the following data: