Mean, Median, and Mode
What can we learn from looking at a group of numbers?
In Machine Learning (and in mathematics) there are often three values that interests us:
This java programming code is used to find the mean, median, mode. You can select the whole java code by clicking the select option and can use it. When you click text, the code will be changed to text format. This java program code will be opened in a new pop up window once you click pop-up from the right corner. C program to find mean, median, variance and standard deviation Write a C program to find mean, median, variance and standard deviation for given set of numbers. Harry potter deathly hallows part 2 download.
- Mean - The average value
- Median - The mid point value
- Mode - The most common value
Mean Median Mode Formula
Example: We have registered the speed of 13 cars:
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
What is the average, the middle, or the most common speed value?
Mean
The mean value is the average value.
To calculate the mean, find the sum of all values, and divide the sum by the number of values:
(99+86+87+88+111+86+103+87+94+78+77+85+86) / 13 = 89.77
The NumPy module has a method for this. Learn about the NumPy module in our NumPy Tutorial.
Example
Use the NumPy
mean()
method to find the average speed: import numpy
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = numpy.mean(speed)
print(x)
Run example »speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = numpy.mean(speed)
print(x)
![Use Use](https://i.ytimg.com/vi/qmYP1um0RXE/maxresdefault.jpg)
Median
The median value is the value in the middle, after you have sorted all the values:
77, 78, 85, 86, 86, 86,
87
, 87, 88, 94, 99, 103, 111
It is important that the numbers are sorted before you can find the median.
The NumPy module has a method for this:
Example
Use the NumPy
median()
method to find the middle value: import numpy
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = numpy.median(speed)
print(x)
Try it Yourself »speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = numpy.median(speed)
print(x)
Cummins qsm11 engine manual. If there are two numbers in the middle, divide the sum of those numbers by two.
77, 78, 85, 86, 86,
86, 87
, 87, 94, 98, 99, 103
(86 + 87) / 2 =
86.5
Example
Using the NumPy module:
import numpy
speed = [99,86,87,88,86,103,87,94,78,77,85,86]
x = numpy.median(speed)
print(x)
Try it Yourself »speed = [99,86,87,88,86,103,87,94,78,77,85,86]
x = numpy.median(speed)
print(x)
Mode
The Mode value is the value that appears the most number of times:
99,
86
, 87, 88, 111,
86
, 103, 87, 94, 78, 77, 85,
86
= 86
The SciPy module has a method for this:
Example
Microsoft visual studio 2012 torrent tpb. Use the SciPy
mode()
method to find the number that appears the most: from scipy import stats
speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = stats.mode(speed)
print(x)
Try it Yourself »speed = [99,86,87,88,111,86,103,87,94,78,77,85,86]
x = stats.mode(speed)
print(x)
Chapter Summary
Better body sims 4. The Mean, Median, and Mode are techniques that are often used in Machine Learning, so it is important to understand the concept behind them.
Java arrays: statistics information
Exercise: Write a Java program to answer about the statistical information such as arithmetic mean, median, mode, and standard deviation of an integer data set. The data points are input by the user from keyboard. This program will display the output similar to the one shown below:
If you are not sure about statistical information such as arithmetic mean, median, mode, and standard deviation, you will need to read this page:
Flash unlock iphone. Solution:
Crossover software for mac. import java.util.Scanner;
public class StatisticsInfo
{
public static void main(String[] args)
{
showStatistics();
}
static void showStatistics(){
//
int n;
float mean,median,std;
Scanner sc=new Scanner(System.in);
System.out.print('Enter number of data points:');
n=sc.nextInt();
if (n < 3)
{
System.out.println('The number of data points should be greater than 2.');
}
else
{
//declare an array of n size to store integral data points
int[] dataset = new int[n];
//allow user inputs
int i = 0;
for (i = 0; i < n; i++)
{
System.out.print('['+i+']:');
dataset[i] = sc.nextInt();
}
//sort the data set
bubblesort(dataset, n);
//calculate the mean
int sum = 0;
int j = 0;
while (j < n)
{
sum = sum + dataset[j];
j++;
}
mean = (float)sum / n;
//calculate median
//If n is odd, median=dataset[n/2]
//If n is even, median=(dataset[n/2]+dataset[1+n/2])/2
//The index of array starts from 0, so you need to subtract 1 from the indices used in calculating the median
if (n % 2 != 0) median = dataset[n / 2];
else median = (dataset[(n / 2) - 1] + dataset[n / 2]) / (float)2;
//calculate the mode
int[][] mode = new int[n][2];
//initialize 2D array storing numbers of occurences, and values
for (i = 0; i < 2; i++)
for (j = 0; j < n; j++) mode[j][i] = 0;
mode[0][0] = 1;
for (i = 0; i < n; i++)
for (j = 0; j < n - 1; j++)
if (dataset[i] dataset[j + 1]) { ++mode[i][0]; mode[i][1] = dataset[i]; }
int max;
int k = 0;
max = mode[0][0];
for (j = 0; j < n; j++)
if (max < mode[j][0]) { max = mode[j][0]; k = j; }
//calculate standard deviation,std
float temp = 0.0f;
for (j = 0; j < n; j++)
{
temp = temp + (float)Math.pow(dataset[j] - mean, 2);
}
std = (float)Math.sqrt(temp / (n - 1));
//Show results
System.out.println('Statistical Information:');
System.out.println(');
System.out.println('Arithmetic mean:'+mean);
System.out.println('Median:'+median);
if (mode[k][1] != 0)
System.out.println('Mode:'+ mode[k][1]);
else System.out.println('Mode: no mode');
System.out.println('Standard deviation:'+std);
}
//
}
public class StatisticsInfo
{
public static void main(String[] args)
{
showStatistics();
}
static void showStatistics(){
//
int n;
float mean,median,std;
Scanner sc=new Scanner(System.in);
System.out.print('Enter number of data points:');
n=sc.nextInt();
if (n < 3)
{
System.out.println('The number of data points should be greater than 2.');
}
else
{
//declare an array of n size to store integral data points
int[] dataset = new int[n];
//allow user inputs
int i = 0;
for (i = 0; i < n; i++)
{
System.out.print('['+i+']:');
dataset[i] = sc.nextInt();
}
//sort the data set
bubblesort(dataset, n);
//calculate the mean
int sum = 0;
int j = 0;
while (j < n)
{
sum = sum + dataset[j];
j++;
}
mean = (float)sum / n;
//calculate median
//If n is odd, median=dataset[n/2]
//If n is even, median=(dataset[n/2]+dataset[1+n/2])/2
//The index of array starts from 0, so you need to subtract 1 from the indices used in calculating the median
if (n % 2 != 0) median = dataset[n / 2];
else median = (dataset[(n / 2) - 1] + dataset[n / 2]) / (float)2;
//calculate the mode
int[][] mode = new int[n][2];
//initialize 2D array storing numbers of occurences, and values
for (i = 0; i < 2; i++)
for (j = 0; j < n; j++) mode[j][i] = 0;
mode[0][0] = 1;
for (i = 0; i < n; i++)
for (j = 0; j < n - 1; j++)
if (dataset[i] dataset[j + 1]) { ++mode[i][0]; mode[i][1] = dataset[i]; }
int max;
int k = 0;
max = mode[0][0];
for (j = 0; j < n; j++)
if (max < mode[j][0]) { max = mode[j][0]; k = j; }
//calculate standard deviation,std
float temp = 0.0f;
for (j = 0; j < n; j++)
{
temp = temp + (float)Math.pow(dataset[j] - mean, 2);
}
std = (float)Math.sqrt(temp / (n - 1));
//Show results
System.out.println('Statistical Information:');
System.out.println(');
System.out.println('Arithmetic mean:'+mean);
System.out.println('Median:'+median);
if (mode[k][1] != 0)
System.out.println('Mode:'+ mode[k][1]);
else System.out.println('Mode: no mode');
System.out.println('Standard deviation:'+std);
}
//
}
}