Untitled

%Spearman's correlation  without af
n=input("Enter number of observation:");
for i=1:n
     x(i)=input("Enter X value");
     y(i)=input("Enter Y value");
end
a1=sort(x);
b1=sort(y);
e=n;
for i=1:n
    a(i)=a1(e);
    e=e-1;
end
e=n;
for i=1:n
    b(i)=b1(e);
    e=e-1;
end

j=0;
k=0;
for i=1:n
    for j=1:n
        if x(i)==a(j)
            rx(i)=j;
            break;
        end
    end
    for k=1:n
        if y(i)==b(k)
            ry(i)=k;
            break;
        end
    end
end
for i=1:n
    d(i)=rx(i)-ry(i);
    dsq(i)=d(i)*d(i);
end
df=sum(dsq);
num=6*df;
dino=n*((n*n)-1);
ans1=1-(num/dino);
disp("Spearman's correlation Rank = ");
disp(ans1);




with af
clear all
clc
n=input("Enter number of observations:");
for i=1:n
    x(i)=input("Enter X value");
    y(i)=input("Enter Y value");
end
rankx=tiedrank(x);
ranky=tiedrank(y);
for i=1:n
    c1(i)=1;
    c2(i)=1;
    d(i)=rankx(i)-ranky(i);
    s(i)=d(i)*d(i);
end
total=sum(s);
d=n*(n^2-1);
af=0;
for i=1:n
    for j=i+1:n
        if (x(i)==x(j))
            c1(i)=c1(i)+1;
        end
    end
end
for i=1:n
    if (c1(i)>1)
        af = af + (c1(i)^3-c1(i))/12;
    end
end

for i=1:n
    for j=i+1:n
        if (y(i)==y(j))
            c2(i)=c2(i)+1;
        end
    end
end
for i=1:n
    if (c2(i)>1)
        af= af + ((c2(i)^3)-c2(i))/12;
    end
end

a=6*(total+af)/d;
spc=1-a;
disp(spc);



shortcut:
x=input('enter value of x');

y=input('enter value of y');

n=length(x);

[~,rx]=ismember(x,sort(x,'descend'));

[~,ry]=ismember(y,sort(y,'descend'));

d=rx-ry;

sum1=sum(d.^2);

disp('spearmans correlation coefficient:');

r=1-6*sum1/(n*(n^2-1));

disp(r)











%Mean of continuous data
n=input("Enter the number of classes: ");
for i=1:n
    lower(i)=input("Enter lower class limit: ");
    upper(i)=input("Enter upper class limit: ");
    freq(i)=input("Enter frequencies of classes: ");
    mid(i)=(lower(i)+upper(i))/2;
    product(i)=mid(i)*freq(i);
end
disp(lower);
disp(upper);
disp(freq);
total=sum(product);
ft=sum(freq);
mean=total/ft;
disp("Mean = ");
disp(mean);




%Median of continuous data
n=input("Enter the number of classes: ");
for i=1:n
    lower(i)=input("Enter lower class limit: ");
    upper(i)=input("Enter upper class limit: ");
    freq(i)=input("Enter frequencies of classes: ");
end
t=sum(freq)/2;
l=0;
cf=0;
for i=1:n
    cf=cf+freq(i);
        if (t<cf)
            cf=cf-freq(i);
            median=lower(i)+((t-cf)/freq(i))*k;
     disp(“Median class is: “);
     fprintf("%d - %d",lower(i),lower(i+1));
            disp("Median is:");
            disp(median);
            break;
        end
end

%Mode of continuous data
n=input("Enter the number of classes: ");
for i=1:n
    lower(i)=input("Enter lower class limit: ");
    upper(i)=input("Enter upper class limit: ");
    freq(i)=input("Enter frequencies of classes: ");
end

m=max(freq);
index=find(freq==m);
disp(index);
f1=freq(index);
disp(f1);
f0=freq(index-1);
f2=freq(index+1);
k=upper(index)-lower(index);
l1=f1-f0;
l2= 2*f1-f0-f2;
l3=l1/l2;
disp(“Modal class is: “);
fprintf("%d - %d",lower(i),lower(i+1));
mode= lower(index) + k*l3;
disp("Mode is: ");
disp(mode);











%Median of discrete data
n=input("Enter the number of elements: ");
for i=1:n
    marks(i)=input("Enter marks of student: ");
end
for i=1:n
    for j=1:i
        if (marks(i)<marks(j))
            t=marks(i);
            marks(i)=marks(j);
            marks(j)=t;
        end
    end
end
disp(marks);
r=rem(n,2);
if (r==0)
    med=(marks(n/2) + marks(n/2+1))/2;
end
if (r~=0)
    med=marks((n+1)/2);
end
disp("Median is: ");
disp(med);

%Mode of discrete data
n=input("Enter the number of elements: ");
for i=1:n
    marks(i)=input("Enter marks of student: ");
end
max=0;
for i=1:n
    count=0;
    for j=i+1:n
        if marks(i)==marks(j)
            count=count+1;
        end
    end
if (count>max)
    max=count;
    mode=marks(i);
end
end
disp("Mode is: ");
disp(mode)





%Mean Deviation(discreat)
n=input("Enter the number of observations: ");
for i=1:n
    obs(i)=input("Enter values: ");
end
total=sum(obs);
mean=total/n;
for i=1:n
    difference(i)=obs(i)-mean;
    mls(i)=abs(difference(i));
end
total2=sum(mls);
md=total2/n;
disp("Mean Deviation is: ")
disp(md);


%Standard Deviation
n=input("Enter the number of observations: ");
for i=1:n
    obs(i)=input("Enter values: ");
end
total=sum(obs);
mean=total/n;
for i=1:5
    k1(i)=obs(i)-mean;
    k2(i)=k1(i)*k1(i);
end
t1=sum(k2);
var=t1/n;
std=power(var,0.5);
disp("Varience is: ");
disp(var);
disp("Standard deviation is: ");
disp(std);






%Mean Deviation(conitinus)
n=input("Enter the number of classes: ");
for i=1:n
    lower(i)=input("Enter lower class limit: ");
    upper(i)=input("Enter upper class limit: ");
    freq(i)=input("Enter frequencies of classes: ");
    mid(i)=(lower(i)+upper(i))/2;
    product(i)=mid(i)*freq(i);
end
total=sum(product);
ft=sum(freq);
mean=total/ft;
for i=1:n
    difference(i)=mid(i)-mean;
    mls(i)=abs(difference(i));
    product2(i)=mls(i)*freq(i);
end
total2=sum(product2);
md=total2/ft;
disp("Mean Deviation is: ")
disp(md);


%Standard Deviation
n=input("Enter the number of classes: ");
for i=1:n
    lower(i)=input("Enter lower class limit: ");
    upper(i)=input("Enter upper class limit: ");
    freq(i)=input("Enter frequencies of classes: ");
    mid(i)=(lower(i)+upper(i))/2;
    product(i)=mid(i)*freq(i);
end
total=sum(product);
ft=sum(freq);
mean=total/ft;
for i=1:5
    k1(i)=freq(i)*mid(i)*mid(i);
end
t1=sum(k1);
l1=t1/ft;
var=l1-(mean*mean);
std=power(var,0.5);
disp("Varience is: ");
disp(var);
disp("Standard deviation is: ");
disp(std);




KARL PEARSON CO-EFFICIENT OF CORELATION CALCULATION
n=input("Enter number of observation:");
for i=1:n
    x(i)=input("Enter X value");
    y(i)=input("Enter Y value");
    xy(i)=x(i)*y(i);
    sqx(i)=x(i)*x(i);
    sqy(i)=y(i)*y(i);
end
sum1=sum(x);
sum2=sum(y);
sum3=sum(xy);
sum4=sum(sqx);
sum5=sum(sqy);
k1=(n*sum3)-(sum1*sum2);
k2=sqrt((n*sum4)-((sum1)^2));
k3=sqrt((n*sum5)-((sum2)^2));
cor=k1/(k2*k3);
disp("Co relation coefficient is: ");
disp(cor);








regression line
n=input("enter number of obsarvtion - ");
for i=1:n
    x(i)=input("enter x - ");
    y(i)=input("enter y - ");
    xy(i)=x(i)*y(i);
    x2(i)=x(i)*x(i);
end
s1=sum(x);
s2=sum(y);
s3=sum(xy);
s4=sum(x2);
B=[s2;s3]
A=[n s1;s1 s4]
c = linsolve(A,B);
%disp(c);  
fprintf("y= %.2f + %.2fx\n",c(1),c(2));




regression curve
clc
clear all
% quadratic curve fitting
n=input("enter number of observation - ");
for i=1:n
    x(i)=input("enter x");
    y(i)=input("enter y");
    xy(i)=x(i)*y(i);
    x2(i)=x(i)*x(i);
    x2y(i)=x2(i)*y(i);
    x3(i)=x2(i)*x(i);
    x4(i)=x3(i)*x(i);
end
s1=sum(x);
s2=sum(y);
s3=sum(xy);
s4=sum(x2);
s5=sum(x2y);
s6=sum(x3);
s7=sum(x4);
D=[s2;s3;s5];
E=[n s1 s4;s1 s4 s6;s4 s6 s7];
F=linsolve(E,D);
fprintf("y= %.2f + %.2fx + %.2fx2\n",F(1),F(2),F(3));



y=ae^bx
clc
clear all
% quadratic curve fitting
n=input("enter number of observation - ");
for i=1:n
    x(i)=input("enter x");
    y(i)=input("enter y");
    lny(i)=log(y(i));
    xy(i)=x(i)*lny(i);
    x2(i)=x(i)*x(i);
end
s1=sum(x);

s2=sum(y);
s3=sum(xy);
s4=sum(lny);
s5=sum(x2);
A=[n s1;s1 s5];
B=[s4;s3];
c=linsolve(A,B);
fprintf("y= %.2f e^%.2f * x2",exp(c(1)),c(2));


y=ab^x
clc
clear all
% quadratic curve fitting
n=input("enter number of observation - ");
for i=1:n
    x(i)=input("enter x");
    y(i)=input("enter y");
    lny(i)=log(y(i));
    xy(i)=x(i)*lny(i);
    x2(i)=x(i)*x(i);
end
s1=sum(x);

s2=sum(y);
s3=sum(xy);
s4=sum(lny);
s5=sum(x2);
A=[n s1;s1 s5];
B=[s4;s3];

c=linsolve(A,B);
fprintf("y= %.2f* %.2f^x",exp(c(1)),exp(c(2)));






Regression
clc
clear all
% regression
n=input("enter number of observation - ");
for i=1:n
    x(i)=input("enter x - ");
    y(i)=input("enter y - ");
    xy(i)=x(i)*y(i);
    x2(i)=(x(i)*x(i));
    y2(i)=(y(i)*y(i));
end
x2=sum(x2)
y2=sum(y2)
xy=sum(xy)
x=sum(x)
y=sum(y)
meanx=x/n
meany=y/n


bxy=(n*xy-(x*y))/(n*y2-(y*y));
byx=(n*xy-(x*y))/(n*x2-(x*x));
disp("Regression X On Y - ");
fprintf("(x- %.2f) = %.2f (y-%.2f)\n",meanx,bxy,meany);
fprintf("x = %dy + %d\n",bxy,(meanx-(meany*bxy)));
disp("Regression Y On X - ");
fprintf("(y- %.2f) = %.2f (x - %.2f)\n",meany,byx,meanx);
fprintf("y = %dx + %d",byx,(meany-(meanx*byx)));












%Binomial Distribution
n=input("Enter the total number of trails: ");
r=input("Enter the number of successful trails out of n: ");
p=input("Enter probability of success: ");
q=1-p;
factn=factorial(n);
factr=factorial(r);
factnr=factorial(n-r);
ncr=factn/(factr*factnr);
ps=ncr*(p^r)*(q^(n-r));
disp("Probability of success is: ");
disp(ps);

%Poison Distribution
clear all
clc
n=input("Enter the total number of trails: ");
p=input("Enter probability of success: ");
x=input("Enter the number of success: ");
lambda=n*p;
k=0-lambda;
p1=exp(k)*(lambda^x)/factorial(x);
p2=0;
for i=1:x-1
    p2=p2+(exp(k)*(lambda^i)/factorial(i));
end
p3=1-p2-p1;
fprintf("P(t=x)=%d\n",(p1));
fprintf("P(0<t<x)=%d\n",(p2));
fprintf("P(t>x)=%d",(p3));









%Line Graph
x=[0 1 2 3 4 5 6 7 8 9 10];
y=[0 1 4 9 16 25 36 49 64 81 100];
z=[0 1 8 27 64 125 216 343 512 729 1000];
hold on;
plot(x,y,'-s');
title("x vs y");
xlabel('x');
ylabel('y');
xlim([0,10]);
ylim([0,100]);
plot(x,z,'-.');
title("x vs z");
xlabel('x');
ylabel('z');
xlim([0,10]);
ylim([0,1000]);
hold off;
%hold off;
%grid on;



%Pie Graph
a=[20;30;40;30];
pie(a);
title("Pie Chart");






%Bar Graph
b=[126;94;162;57];
barh(b);
title("Bar Graph");
ylabel("Number of Observation");
xlabel("Value");






%BoxPlot
c=[184;152;160;143;168;170];
figure
boxplot(c)
title("Box Plot Graph");