Hey man.........this is an easiest introduction of MATLAB

1. Introduction to MATLAB
Md. Menhazul Abedin
Lecturer, Statistics Discipline
Khulna university
menhaz70@gmail.com

2. What is MATLAB
• High level language for technical computing
• Stands for MATrix LABoratory
• Everything is a matrix - easy to do linear
algebra

3. MATLAB Desktop
Menu and toolbar
CommandHistory
Workspace

4. Valid variables Names
• A valid variable name starts with a letter,
followed by letters, digits, or underscores.
• MATLAB® is casesensitive, so A and a are not the
same variable.
• The maximum length of a variable name is the
value that the namelengthmax command returns.
• You cannot define variables with the same names
as MATLAB keywords, such as if or end. For a
complete list, run the iskeyword command.

5. Matlab keywords….
• Keywords are must not variable name
• 'break' 'case' 'catch' 'classdef' 'continue' 'else'
'elseif' 'end' 'for' 'function' 'global' 'if' 'otherwise'
'parfor' 'persistent' 'return' 'spmd' 'switch' 'try'
'while'

6. How to run?
• If program in command space press “ enter”
• If in open script then block command and
presss F9.

7. Matrices & Vectors
• All (almost) entities in MATLAB are matrices
• Easy to define:
• Use ‘,’ or ‘ ’ to separate row elements
• use ‘;’ to separate rows
>> A = [1 3; 5 8]
A = 1 3
5 8
>> A = [1,3; 5,8]
A = 1 3
5 8

8. Matrices & Vectors
• Order of Matrix -
– m=no. of rows,
– n=no. of columns
• Vectors - special cases
– n = 1 column vector
– m = 1 row vector

m  n

9. Simple algebraic operations
Addition +
Subtraction -
Multiplication *
Division /
Power ^
Logarithm log()
Exponential Exp()
Square root sqrt()
Absolute value abs()

10. Element wise operations…
.*element-by-element multiplication
./element-by-element division
.^ element-by-element power

11. Operators (relational, logical)
• == Equal to
• ~= Not equal to
• < Strictly smaller
• > Strictly greater
• <= Smaller than or equal to
• >= Greater than equal to
• & And operator
• | Or operator

12. Sequences…….
• t =1:10
t =
1 2 3 4 5 6 7 8 9 10
• k =2:-0.5:-1
k =
2 1.5 1 0.5 0 -0.5 -1
• y=[2:2:12]
y=
2 4 6 8 10 12
• B = [1:4; 5:8]
x =
1 2 3 4
5 6 7 8

13. Some practice…….
• Do some mathematical operations as like as
calculator (addition, subtraction,
multiplication, division, log, square root,
power and so on)

14. Matrix...
• a vector x = [1 2 5 1]
x =
1 2 5 1
• a matrix x = [1 2 3; 5 1 4; 3 2 -1]
x =
1 2 3
5 1 4
3 2 -1

15. Special matrix….
• Identity matrix= eye (row,column)
• One matrix= ones(row,column)
• Zero marix= zeros (row,column)

16. Matrix operations…
• Let A be a matrix….
• Determinant= det(A)
• Transpose= A’
• Rank = rank(A)
• Inverse= inv(A)
• Trace = trace(A)
• Eigen value=eig(A)
• Eigen value and vector= [V,D] = eig(A)
• Matrix multiplication= A*B
• Matrix multiplication= A.*B [elementwise]
• Singular values= svd(A)

17. Cont…
• diag diagonal atrix
• triu upper triangular matrix
• tril lower triangular matri
• rand randomly generated matrix
• C=rand(5,4)
• triu(C)
• tril(C)
• diag([0.9092;0.5163;0.2661])

18. Cont…
• Length of a vector= length(x)
• Size or dimension of matrix= size(A)
• Replication of same number=
repmat(number,m,n)

19. Basic statistical building function…
• Let be a sample
• Mean= mean(x)
• Median=median(x)
• Mode= mode(x)
• Variance=var(x)
• Standard deviation=std(x)
• Minimum= min(x)
• Maximum= max(x)
• Summation=sum(x)
nxxxx ,...,, 21

20. Data preprocessing…(Missing value)
• a = magic(3); a(2,2) = NaN
• a = 8 1 6
3 NaN 7
4 9 2
sum(a)
ans =
15 NaN 15
sum(a) ans = 15 NaN 15
sum(a,'omitnan')
ans = 15 10 15
Class of
variables=class(A)

21. Random number generation….
• Normal distribution:
normrnd(mu,sigma) for a single value
normrnd(mu,sigma,m,n) or
normrnd(mu,sigma[m,n]) for matrix having
m row and ncolumn
• Poisson distribution:
poissrnd(lamda)
poissrnd(lamda,m,n)
poissrnd(lamda,[m,n])
Binomial distribution:
binornd(N,P)
binornd(N,P,m,n)
binornd(N,P,[m,n])

22. Cont…
• Geometric distribution:
geornd(p)
geornd(p,m,n)
geornd(p,[m,n])
• Beta distribution:
betarnd(A,B)
betarnd(A,B,m,n)
betarnd(A,B,[m,n])
Exponential distribution:
exprnd(mu)
exprnd(mu,m,n)
exprnd(mu,[m,n])
Gamma distribution:
gamrd(A,B)
gamrnd(A,B,m,n)
gamrnd(A,B,[m,n])

23. Cont…
• Standard normal distribution:
randn return single value
randn(n) return n-by-n square matrix
randn(r,c) return r-by-c matrx

24. Covariance of Matrix
• C = cov(A,B)
returns the covariance between two random
variables A and B.
• C = cov(A)
returns the matrix of correlation
coefficient for A, where the columns
of A represent random variables and the rows
represent observations.

25. Example…
• A = [5 0 3 7; 1 -5 7 3; 4 9 8 10];
C = cov(A)
• A = [3 6 4]; B = [7 12 -9];
cov(A,B)

26. Correlation coefficient…
• R = corrcoef(A)
returns the matrix of correlation
coefficient for A, where the columns
of A represent random variables and the rows
represent observations.
• R= corrcoef(A,B)
returns coefficients between two random
variables A and B.

27. Example…..
• x = randn(6,1);
• y = randn(6,1);
• A = [x y 2*y+3];
• R = corrcoef(A)
• A = randn(10,1);
• B = randn(10,1);
• R = corrcoef(A,B)

28. Ploting…
• x vector
• y vector
• Z vector
plot(x,y) 2D line diagram
plot(x,y,z) 3D line diagram
scatter(x,y) scatter diagram
scatter(x,y,z) 3D scatter diagram
bar(x) bar diagram
bar3(x) 3D bar diagram
hist(x) histogram
boxplot(x) boxplot
• xlabel(‘text')
• ylabel(‘text')
scatter(x,y,'d')
scatter(x,y,'*')
scatter(x,y,'b')
scatter(x,y,'p')
scatter(x,y,’+')
scatter(x,y,‘x')
theta = linspace(0,1,500);
x = exp(theta).*sin(100*theta);
y = exp(theta).*cos(100*theta);
s = scatter(x,y)
You may change color like scatter(x,y,’x’,’r’)

29. Regression…
load moore
y=moore(:,6)
x1=ones(length(y),1)
x2=moore(:,1:5)
x=[x1 x2]
% now perform regression %
[b,bint,r,rint,stats]=regress(y,x)

30. Test…
• %Single mean test
load stockreturns
x = stocks(:,3)
length(x)
[h,p,ci,stats] = ttest(x)
load stockreturns
x = stocks(:,3);
h = ttest(x,0,0.01)
• %paired mean test
load examgrades
x = grades(:,1);
y = grades(:,2);
[h,p] = ttest(x,y)

31. Cont…
%paired mean test
load examgrades
x = grades(:,1);
y = grades(:,2);
[h,p] = ttest2(x,y)
load examgrades
x = grades(:,1);
y = grades(:,2);
[h,p] = ttest(x,y,0.01)
Similar way F-test , z-test, chi-square test etc
%t-Test for a Hypothesized Mean
load examgrades
x = grades(:,1);
h = ttest(x,75)
%One-Sided t-Test
load examgrades
x = grades(:,1);
h = ttest(x,65,'right')

32. ANOVA…
% ANOVA one way
y = meshgrid(1:5);
y = y + normrnd(0,1,5,5)
p = anova1(y)
%ANOVA two way........
load popcorn
popcorn
[p,tbl] = anova2(popcorn,3);

33. Importing data…
• Excel data
• Watch the vedio
• File import data fix direcory
open ( tick generate matlab code) next
finish
https://www.youtube.com/watch?v=-
mZci3mNjlU

34. • clc clear commad window
• whos data size, class, bytes etc
• who provide variable names
• help mean
• help who
• help median
• help regression
• help plot

35. Thanks