This is my one dimensional array `A`

. containing 10 numbers

```
A = [-8.92100000000000 10.6100000000000 1.33300000000000 ...
-2.57400000000000 -4.52700000000000 9.63300000000000 ...
4.26200000000000 16.9580000000000 8.16900000000000 4.75100000000000];
```

I want the loop to go through like this; (calculating mean interval wise) - Interval length of 2,4,8

`(a(1)+a(2))/2`

- value stored in one block of a matrix say m= zeros(10)
- then
`(a(1)+a(2)+a(3)+a(4))/4`

------ mean-----
- then
`(a(1)+a(2)..... a(8))/8`

then shift index;

`(a(2)+a(3))/2;`

- mean
`(a(2)+a(3)+a(4)+a(5))/4`

`(a(2)+a(3)...a(9))/8`

**SO basically 2^n length interval**

# Best How To :

You could do this using `conv`

without loops

```
avg_2 = mean([A(1:end-1);A(2:end)])
avg_4 = conv(A,ones(1,4)/4,'valid')
avg_8 = conv(A,ones(1,8)/8,'valid')
```

**Output for the sample Input:**

```
avg_2 =
0.8445 5.9715 -0.6205 -3.5505 2.5530 6.9475 10.6100 12.5635 6.4600
avg_4 =
0.1120 1.2105 0.9662 1.6985 6.5815 9.7555 8.5350
avg_8 =
3.3467 5.4830 4.7506
```

Finding **Standard Deviation** for an example (`std_4`

)

```
%// each 1x4 sliding sub-matrix is made a column
%// for eg:- if A is 1x6 you would get 1-2-3-4, 2-3-4-5, 3-4-5-6 each as a column
%// ending with 3 columns. for 1x10 matrix, you would get 7 columns
reshaped_4 = im2col(A,[1 4],'sliding'); %// change 4 to 2 or 8 for other examples
%// calculating the mean of every column
mean_4 = mean(reshaped_4);
%// Subtract each value of the column with the mean value of corresponding column
out1 = bsxfun(@minus,reshaped_4,mean_4);
%// finally element-wise squaring, mean of each column
%// and then element-wise sqrt to get the output.
std_4 = sqrt(mean(out1.^2))
```

**Output for the sample Input:**

```
std_4 =
7.0801 5.8225 5.4304 5.6245 7.8384 4.5985 5.0906
```

**Full code for OP**

```
clc;
clear;
close all;
A = [-8.92100000000000 10.6100000000000 1.33300000000000 ...
-2.57400000000000 -4.52700000000000 9.63300000000000 ...
4.26200000000000 16.9580000000000 8.16900000000000 4.75100000000000];
reshaped_2 = im2col(A,[1 2],'sliding'); %// Length Two
mean_2 = mean(reshaped_2);
out1 = bsxfun(@minus,reshaped_2,mean_2);
std_2 = sqrt(mean(out1.^2))
reshaped_4 = im2col(A,[1 4],'sliding'); %// Four
mean_4 = mean(reshaped_4);
out1 = bsxfun(@minus,reshaped_4,mean_4);
std_4 = sqrt(mean(out1.^2))
reshaped_8 = im2col(A,[1 8],'sliding'); %// Eight
mean_8 = mean(reshaped_8);
out1 = bsxfun(@minus,reshaped_8,mean_8);
std_8 = sqrt(mean(out1.^2))
```