numpy.var[arr, axis = None]
: Tính phương sai của dữ liệu đã cho [các phần tử mảng] dọc theo trục được chỉ định [nếu có]. Compute the variance of the given data [array elements] along the specified axis[if any].
Thí dụ :
x = 1 1 1 1 độ lệch chuẩn 1 = 0. Phương sai = 0
Standard Deviation = 0 . Variance = 0Y = 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4
Bước 1: Giá trị trung bình của phân phối 4 = 7STEP 2: tổng hợp [x - x.mean []] ** 2 = 178Step 3: tìm kiếm trung bình = 178 /20 = 8,9 kết quả này là phương sai. Mean of distribution 4 = 7
Step 2 : Summation of [x – x.mean[]]**2 = 178
Step 3 : Finding Mean = 178 /20 = 8.9
This Result is Variance.
Thông số :
ARR: [Array_like] Mảng đầu vào.axis: [int hoặc bộ dữ liệu của trục int] dọc theo đó chúng tôi muốn tính toán phương sai. Nếu không, nó sẽ xem xét
arr
để được làm phẳng [hoạt động trên tất cả các trục]. Trục = 0 có nghĩa là phương sai dọc theo cột và trục = 1 có nghĩa là phương sai dọc theo hàng. Mảng phải có cùng kích thước như đầu ra dự kiến. [array_like] input array.
axis : [int or tuples of int] axis along which we want to calculate the variance. Otherwise, it will considerarr
to be flattened [works on all the axis]. axis = 0 means variance along the column and axis = 1 means variance along the row.
out : [ndarray, optional] Different array in which we want to place the result. The array must have the same dimensions as expected output.
dtype : [data-type, optional] Type we desire while computing variance.Kết quả: Phương sai của mảng [giá trị vô hướng nếu trục không có] hoặc mảng có giá trị phương sai dọc theo trục được chỉ định. Variance of the array [a scalar value if axis is none] or array with variance values along specified axis.
Mã số 1:
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]0
arr
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]3
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]4
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]8
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.40924223
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.409246
Variance of sample set is 0.409247
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000060
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000061
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000064
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000065
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000067
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000064
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000065
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of Sample set is 0.36566666666666673
Đầu ra:
arr : [20, 2, 7, 1, 34] var of arr : 158.16 var of arr : 158.16 var of arr : 158.16
& nbsp; mã số 2:
Code #2:
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]0
arr
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]3
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]4
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]8
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.40924223
0.36566666666630539
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]3
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points1
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points3
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points7
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
0.36566666666630538
0.36566666666630539
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]3
numpy.var[arr, axis = None]
3var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
numpy.var[arr, axis = None]
7var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
arr
20.36566666666630539
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]3
arr
5var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
arr
7var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.409242
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]8
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
import
4Variance of sample set is 0.409244
Variance of sample set is 0.409245
import
7Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000061
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000064
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000065
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000067
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000064
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.176130000000000065
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of Sample set is 0.36566666666666673
Đầu ra:
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]
Mô -đun thống kê cung cấp các công cụ rất mạnh mẽ, có thể được sử dụng để tính toán bất cứ điều gì liên quan đến số liệu thống kê. Phương sai [] là một trong các hàm như vậy. Hàm này giúp tính toán phương sai từ một mẫu dữ liệu [mẫu là một tập hợp con của dữ liệu dân cư]. & NBSP; Chức năng phương sai [] chỉ nên được sử dụng khi phương sai của mẫu cần được tính toán. Có một hàm khác được gọi là pvariance [], được sử dụng để tính toán phương sai của toàn bộ dân số. Trong các thống kê thuần túy, phương sai là độ lệch bình phương của một biến so với giá trị trung bình của nó. Về cơ bản, nó đo lường sự lây lan của dữ liệu ngẫu nhiên trong một tập hợp từ giá trị trung bình hoặc trung bình của nó. Giá trị thấp cho phương sai chỉ ra rằng dữ liệu được nhóm lại với nhau và không được phân tách rộng rãi, trong khi giá trị cao sẽ chỉ ra rằng dữ liệu trong tập hợp đã cho nhiều hơn nhiều so với giá trị trung bình. & NBSP; Phương sai là một công cụ quan trọng trong Các ngành khoa học, trong đó phân tích thống kê dữ liệu là phổ biến. Đó là bình phương độ lệch chuẩn của bộ dữ liệu đã cho và còn được gọi là thời điểm trung tâm thứ hai của phân phối. Nó thường được đại diện bởi & nbsp; trong thống kê thuần túy. Varariance được tính bằng công thức sau: & nbsp; & nbsp;variance[] is one such function. This function helps to calculate the variance from a sample of data [sample is a subset of populated data].
variance[] function should only be used when variance of a sample needs to be
calculated. There’s another function known as pvariance[], which is used to calculate the variance of an entire population.
In pure statistics, variance is the squared deviation of a variable from its mean. Basically, it measures the spread of random data in a set from its mean or median value. A low value for variance indicates that the data are clustered together and are not spread apart widely, whereas a high value would indicate that the data in the given set are much more spread apart
from the average value.
Variance is an important tool in the sciences, where statistical analysis of data is common. It is the square of standard deviation of the given data-set and is also known as second central moment of a distribution. It is usually represented by
Variance is calculated by the following formula :
Nó được tính toán theo giá trị trung bình của hình vuông bình phương trung bình & nbsp;
Cú pháp: Phương sai [[Dữ liệu], Xbar] tham số: & nbsp; [Dữ liệu]: Một số lặp có số có giá trị thực. & NBSP; Xbar [Tùy chọn] Các giá trị được truyền dưới dạng tham số. Exexceptions: & nbsp; StatisticerError được nâng lên cho dữ liệu-set nhỏ hơn 2 giá trị được truyền dưới dạng tham số. & nbsp; variance[ [data], xbar ]
Parameters :
[data] : An iterable with real valued numbers.
xbar [Optional] : Takes actual mean of data-set as value.
Returnype : Returns the actual variance of the values passed as parameter.
Exceptions :
StatisticsError is raised for data-set less than 2-values passed as parameter.
Throws impossible values when the value provided as xbar doesn’t match actual mean of the data-set.
Mã số 1: & NBSP;
Python3
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]14
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]15
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.1761300000000000625
Variance of sample set is 0.409244
Variance of sample set is 0.409245
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]32
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]33
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]35
Đầu ra: & nbsp; & nbsp;
Variance of sample set is 0.40924
& nbsp; & nbsp; Ứng dụng: & nbsp; phương sai là một công cụ rất quan trọng trong thống kê và xử lý một lượng dữ liệu khổng lồ. Giống như, khi không rõ giá trị trung bình [trung bình mẫu] thì phương sai được sử dụng làm công cụ ước tính sai lệch. Các quan sát trong thế giới thực như giá trị của sự gia tăng và giảm tất cả các cổ phiếu của một công ty trong suốt cả ngày không thể là tất cả các bộ quan sát có thể. Do đó, phương sai được tính toán từ một tập dữ liệu hữu hạn, mặc dù nó đã giành được trận đấu khi tính toán toàn bộ dân số, nhưng nó vẫn sẽ cho người dùng ước tính đủ để đưa ra các tính toán khác. & NBSP;
Code #2 : Demonstrates variance[] on a range of data-types
Python3
Có một hàm phương sai trong Python?
Thống kê Python | Phương sai [] phương sai [] là một trong số các hàm như vậy. Hàm này giúp tính toán phương sai từ một mẫu dữ liệu [mẫu là một tập hợp con của dữ liệu đông dân]. Hàm phương sai [] chỉ nên được sử dụng khi phương sai của mẫu cần được tính toán.
Phương sai được tính toán như thế nào?
Trong thống kê, phương sai đo lường sự thay đổi từ trung bình hoặc trung bình. Nó được tính toán bằng cách lấy sự khác biệt giữa mỗi số trong tập dữ liệu và giá trị trung bình, sau đó bỏ qua sự khác biệt để làm cho chúng tích cực và cuối cùng chia tổng các bình phương cho số lượng giá trị trong tập dữ liệu.
Hàm Python nào được sử dụng để tính toán trung bình và phương sai?
Variance of sample set is 0.4092404
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.4092406
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6____210
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]6
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]26
Variance of sample set is 0.4092410
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]26
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5__153____18
Variance of sample set is 0.4092419
Variance of sample set is 0.4092420
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]51
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points3
Variance of sample set is 0.4092410
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]8
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points7
Variance of sample set is 0.4092428
Variance of sample set is 0.4092429
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.409245
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]20
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092434
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092436
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092438
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5____240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]60
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092444
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.4092446
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092449
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.4092451
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092454
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.4092456
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092459
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.4092461
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092464
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.4092466
Đầu ra: & nbsp; & nbsp;
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.17613000000000006
& nbsp; & nbsp; mã số 3: Thể hiện việc sử dụng tham số Xbar & nbsp; & nbsp;
Code #3 :
Demonstrates the use of xbar parameter
Python3
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]14
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]15
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.409245
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092474
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092476
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092440
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5____280
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092438
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]60
Variance of sample set is 0.4092484
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.4092486
Variance of sample set is 0.409244
Variance of sample set is 0.409245
Variance of sample set is 0.4092489
0.36566666666630539
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.40924929
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.4092494
Đầu ra: & nbsp; & nbsp;
Variance of Sample set is 0.3656666666666667
& nbsp; & nbsp; mã số 3: Thể hiện việc sử dụng tham số Xbar & nbsp; & nbsp;
Code #4 : Demonstrates the
Error when value of xbar is not same as the mean/average value
Python3
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]14
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]15
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.409245
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092474
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092476
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092440
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5____280
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092438
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]60
Variance of sample set is 0.4092484
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.4092486
0.36566666666630539
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]34
Variance of sample set is 0.40924929
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.4092494
Đầu ra: & nbsp; & nbsp;
0.3656666666663053
& nbsp; & nbsp; mã số 3: Thể hiện việc sử dụng tham số Xbar & nbsp; & nbsp;
Code #4 : Demonstrates StatisticsError
Python3
import
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]14
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]15
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]2
Variance of sample set is 0.409245
Variance of sample set is 0.409240
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092474
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092476
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092440
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5____280
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]5
Variance of sample set is 0.4092438
var of arr, axis = None : 236.14000000000004 var of arr, axis = 0 : [ 57.1875 312.75 345.6875 9.25 0. ] var of arr, axis = 1 : [ 0. 77.04 421.84 269.04]60
Variance of sample set is 0.409244
Variance of Sample 1 is 15.80952380952381 Variance of Sample 2 is 3.5 Variance of Sample 3 is 61.125 Variance of Sample 4 is 1/45 Variance of Sample 5 is 0.1761300000000000627
Đầu ra: & nbsp; & nbsp;
Traceback [most recent call last]: File "/home/64bf6d80f158b65d2b75c894d03a7779.py", line 10, in print[statistics.variance[sample]] File "/usr/lib/python3.5/statistics.py", line 555, in variance raise StatisticsError['variance requires at least two data points'] statistics.StatisticsError: variance requires at least two data points
& nbsp; & nbsp; mã số 3: Thể hiện việc sử dụng tham số Xbar & nbsp; & nbsp;
Applications :
Variance is a very important tool in Statistics and handling huge amounts of data. Like, when the omniscient mean is
unknown [sample mean] then variance is used as biased estimator. Real world observations like the value of increase and decrease of all shares of a company throughout the day cannot be all sets of possible observations. As such, variance is calculated from a finite set of data, although it won’t match when calculated taking the whole population into consideration, but still it will give the user an estimate which is enough to chalk out other calculations.