Matlab exercises -- basic data processing

matlab Series articles ： Catalog

One 、 subject

Read the attachment sd.xlsx, Calculate the following statistics ：

• mean value
• variance
• Standard deviation
• Maximum
• minimum value
• range
• Median
• quantile
• The number of
• Coefficient of variation
• The moment of origin
• Center distance
• skewness
• kurtosis （ The above calculation sd In the first column )
• Covariance and correlation coefficient of the data in the first and second columns

Resource link ：https://download.csdn.net/download/qq_21484461/85801116?spm=1001.2014.3001.5503

Two 、 answer

1. Reading data

>> [num1]=xlsread('F:\sd.xlsx',1,'A1:B191')		% Before reading 1、2 Column 
>>
>> [num2]=xlsread('F:\sd.xlsx',1,'D1:E191')		% Before reading 4、5 Column 
>>
>> [num3]=xlsread('F:\sd.xlsx',1,'G1:H40')		% Before reading 7、8 Column 

2. Calculating mean

>> mean(num1(:,[1]))

ans =

    2.9634

3. Variance estimation

>> var(num1(:,[1]))

ans =

    0.9337

4. Find standard deviation

>> std(num1(:,[1]))

ans =

    0.9663

5. For maximum

>> max(num1(:,[1]))

ans =

    6.4000

6. For the minimum

>> min(num1(:,[1]))

ans =

    0.5000

7. Seeking the range

>> max(num1(:,[1]))-min(num1(:,[1]))

ans =

    5.9000

8. Find the median

>> median(num1(:,[1]))

ans =

    2.8000

9. Find the quantile

>> prctile(num1(:,[1]),40)		%40 quantile 

ans =

    2.5000

10. The number of

>> mode(num1(:,[1]))

ans =

    2.2000

11. Coefficient of variation

>> std(num1(:,[1]))/mean(num1(:,[1]))

ans =

    0.3261

12. The moment of origin

>> sum(num1(:,[1]).^2)/length(num1(:,[1]))		%2 Moment of origin of order 

ans =

    9.7103

or

>> mean(num1(:,[1]).^2)

ans =

    9.7103

13. Center distance

>> for i = 1:length(num1(:,[1]))
x1(i) = num1(i) - mean(num1(:,[1]))
end
>>
>> mean(x1.^2)

ans =

    0.9288

14. Seeking skewness

>> skewness(num(:,[1]))

ans =

    0.3339

14. kurtosis

>> kurtosis(num(:,[1]))

ans =

    2.9240

15. Covariance and correlation coefficient of the data in the first and second columns

① covariance

First column ：

>> cov(num1(:,[1]))

ans =

    0.9337

Second column ：

>> cov(num1(:,[2]))

ans =

    5.3527

Covariance matrix

>> cov(num1(:,[1]),num1(:,[2]))

ans =

    0.9337    0.3703
    0.3703    5.3527

② The correlation coefficient

>> corr(num1(:,[1]),num1(:,[2]))

ans =

    0.1656