Question

please solve this in matlab platform, will solving write this mydata=importdata(‘’cars.txt’’,”|”,1) like this i hv the cars.txt data in my pc.

Analyze the data in cars.txt which you have to download from the section of "Sinif Dosyalari on Ninova. [35 points] Write one script to answer all the parts. Save your script named as "final". a. There exists linearity between "length" and "curb". Plot the data in order to observe the 3. linearity b. Let "curb" be the dependent variable, and "length" be the independent variable. Generate a linear regression model (i.e. y-, * x + β°). Plot the regression line. Forecast values of curb where length is [100 150 200]. c. d. Reminder (1): myData- importdata ("myData.txt", "I,1) y-myData. data (,) x-myData. data (:,2)

Answer 1

myData=importdata("cars.txt","|",1) ;
curb = myData.data(:,1); % dependent variable
lngth = myData.data(:,2); % independent variable; name 'lngth' is to avoid
                            % confusion with in-built MATLAB function length

% a. observe whether or not dependent variable curb has linear relation with independent variable lngth

figure;plot(lngth,curb)

% b. fit regression line using least square method

mean_l = mean(lngth);
mean_c = mean(curb);

for i=1:length(lngth)
    std_l(i) = (lngth(i) - mean_l)^2;
    cov_lc(i) = (lngth(i) - mean_l)*(curb(i) - mean_c);
end

m = sum(cov_lc)/sum(std_l); % slope of regression line
b = mean_c -m*mean_l; % intercept of regression line
curb_fit = m*lngth + b; % equation of regression line

% c. plot the regression line

figure;plot(lngth, curb_fit)

% d. forecast values of curb for length = [100 150 200]

curb_100 = m*100 + b;
curb_150 = m*150 + b;
curb_200 = m*200 + b;