Calculate correlation and probable error between physical parameters (temperature and humidity)Number of families(x)=2Number of sites(n)= 1Temperature(y) in autumn= 24.1Humidity(y) in autumn= 3520 1 19Calculate correlation and probable error between physical parameters (temperature and humidity)Using the following formulacoefficient of correlation (r).r = n([xy)-([x) (Ey) V[n(Ex 2)-(Ex) 2][n(Ey2)-([y) 2]I

The given values of x and y variables as shown belowAutumn:Temperature (y): 24.1Humidity (y):…

Answered: Calculate correlation and probable…

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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Q1/ A sample of 6 beams was selected the value of their deflections (x variable) and their weight is demonstrated in the following table. Find the regression equation and what is the predicted weight when deflection is Sequence your name in the list. Serial no. Def. (x) Weight (y) 1 7 12 8 8 12 4 5 10 5 6 11 9 13
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Forest Fires and Acres Burned Numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned for 6 recent years are shown. The regression line equation is =y′+−45.79501.34704x. The correlation coefficient is =r0.858. Compute the standard error of the estimate rounded to at least two decimal places, if appropriate. Assume =α0.05 The standard error of the estimate should or should not be calculated. S est= Number of fires x 57 45 72 69 58 47 Number of acres burned y 30 15 62 42 19 26
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What is the R2 value for the relationship between Height and Weight?
Due in 3 hours, 41 minutes. Due Sat 04/18/2020 11:59 pm Show Intro/Instructions A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: у-ах+b a=6.704 b=30.59 p2=0.972196 r=0.986 Use this to predict the final exam score of a student who studies 8.5 hours per week, and please round your answer to a whole number. Hint: Help License Points possible: 1 This is attempt 1 of 3. Message instructor about this question Submit
Allustration 27. For a bivariate data, you are given the following information: E(X- 58) = 46 'EXX - 58)? = 3086 E(Y- 58) = 9 E(Y- 58)* = 483 E(X – 58) (Y– 58) = 1095 Number of pairs of observations = 7. You are required to determine (i) the two regression equations and (ii) the co-efficient of correlation between X and Y series. %3D %3!
A regression was done for 20 cities with the latitude (Latitude), a measurement of the distance of a location on the Earth from the equator in degrees and the average January temperatures (Temp) as the dependent variable measure in. The regression equation is a) The value of the slope is [Select ] [Select] TEMP=48.4 -0.31 x LATITUDE b) The predicted average January temperatures for the 20 cities for a latitude of 45 degrees is [Select] ✓. If in fact the [Select] average January temperature for a latitude of 45 degrees is 40° F , the residual is [Select] which is a(n) [Select] which means c) The coefficient of determination is R²: 66.2%. This value means [Select] The correlation r, is which means [Select] d) The y-intercept is [Select] the problem interprets to [Select] make sense in the context of the problem? [Select] Formulas: r = ±√R² Residual actual y - predicted y 0.7<|rl≤1 very strong 0.5

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