Can someone help me with my code?

Question

Onur Metin Mertaslan 2020-5-23

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/530953-can-someone-help-me-with-my-code

回答： Cris LaPierre 2020-12-20

clear all, clc, close all;
N=1:99;
alfa=0.05;
z=1.96;
t= 1.984;  %two-tailed t critical for 95% confidence interval
N_l=(4.459595959595959e+03+4.419191919191920e+03)/2; %population lower mean
N_u=(5.833333333333333e+03+6.080808080808080e+03)/2; %population upper mean
Sample_l=[];
Sample_u=[];
gpa=[2.25,2.75,2.75,2.75,2.75,2.75,2.75,2.75,3.25,3.75,3.75,2.25,2.25,2.25,2.25,2.25,2.75,2.75,2.75,2.75,2.25,2.75,2.75,2.75,2.75,2.75,2.75,2.75,2.75,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.75,2.25,2.25,2.25,2.25,2.75,2.75,2.75,2.75,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,2.25,2.25,2.75,2.75,2.75,2.75,2.75,2.75,2.75,2.75,3.25,3.25,3.25,3.25,3.25,3.25,3.75,3.75,2.25,2.25,2.25,2.25,2.25,2.25,2.25,2.75,2.75,2.75,2.75,2.75,2.75,2.75,2.75,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.25,3.75];
for i=1:11
   Sample_l(i)=2500;
   Sample_u(i)=3500;
end;
for j=12:20
    Sample_l(j)=3500;
    Sample_u(j)=4000;
end;
for k=21:38
    Sample_l(k)=4000;
    Sample_u(k)=4500;
end;
for t=39:54
    Sample_l(t)=4500;
    Sample_u(t)=5000;
end;
for z=55:72
    Sample_l(z)=5000;
    Sample_u(z)=5500;
   end;
for u=73:99
    Sample_l(u)=5500;
    Sample_u(u)=9000;
end;
A=sum(Sample_l)/99; %mean of the lower limit
B=sum(Sample_u)/99; %mean of the upper limit
Var_l=var(Sample_l); %var of the lower limit
Var_u=var(Sample_u); %var of the upper limit
Std_l=std(Sample_l); %Standart deviation of the lower limit
Std_u=std(Sample_u); %Standart deviation of the upper limit

Hello everyone, I am trying to find linear regration between "gpa" and "Sample_l" but I could not do it in matlab. Actually I could not understand how to do it. Is there anyone who can help me?

Thanks a lot!

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Answer 1

Cris LaPierre 2020-12-20

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https://ww2.mathworks.cn/matlabcentral/answers/530953-can-someone-help-me-with-my-code#answer_580200

There are a couple ways to do this in MATLAB. I'll go with the one that doesn't require any additional toolboxes.

You can do this with polyfit, which tries to fit a polynomial of a specified order to the X and Y data. Linear regression is just fitting a polynomial of first order (

).

You can follow this example.