File:T distribution 30df enhanced.svg
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DescriptionT distribution 30df enhanced.svg |
English: Student's t-distribution with 30 degrees of freedom. Enhanced imaging |
Date | |
Source | Own work |
Author | IkamusumeFan |
SVG development InfoField | This diagram was created with Matplotlib. |
Plot using Python Matplotlib.
Licensing edit
I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
Python (Matplotlib) edit
import numpy as np
import matplotlib.pyplot as plt
import scipy.special as sp
X = np.arange(-4, 4, 0.01) # range of the graph
plt.clf()
plt.figure(figsize=(4,4))
plt.axes([0.17,0.13,0.79,0.8])
plt.hold(True)
Q = [] # No curves at first.
# Draw the previous Student's t-distributions
nu = 30 # freedom degree = 30
for previous_nu in range(1,nu):
mu = 0 # mean = 0
A = np.exp(sp.gammaln((previous_nu+1)/2.0));
B = np.exp(sp.gammaln(previous_nu/2.0))*np.sqrt(previous_nu*np.pi);
C = (1+X*X/previous_nu)**(-(previous_nu+1)/2.0);
Y = A*C/B;
a = plt.plot(X, Y, '-', color='green', lw=1)
Q.append(a)
# Draw the curve of Normal distribution
mu = 0 # mean = 0
sigma = 1 # variance = 1
A = 1/(sigma*np.sqrt(2*np.pi))
B = np.exp(-(X-mu)*(X-mu)/(2*sigma*sigma));
Y = A*B
a = plt.plot(X, Y, '-', color='blue', lw=2)
Q.append(a)
# Draw the curve of Student's t-distribution
mu = 0 # mean = 0
A = np.exp(sp.gammaln((nu+1)/2.0));
B = np.exp(sp.gammaln(nu/2.0))*np.sqrt(nu*np.pi);
C = (1+X*X/nu)**(-(nu+1)/2.0);
Y = A*C/B;
a = plt.plot(X, Y, '-', color='red', lw=2)
Q.append(a)
# Remaining steps to finish drawing the graph.
plt.xlabel("x")
plt.ylabel("P(x)")
plt.xlim(-4,4)
# Saving the output.
plt.savefig("T_distribution_1df.pdf")
plt.savefig("T_distribution_1df.eps")
plt.savefig("T_distribution_1df.svg")
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Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 09:10, 29 April 2016 | 360 × 360 (67 KB) | IkamusumeFan (talk | contribs) | revise based on discussions | |
04:55, 21 July 2013 | 360 × 360 (86 KB) | IkamusumeFan (talk | contribs) | The previous edition is wrong on the degrees of freedom. | ||
04:26, 21 July 2013 | 360 × 360 (86 KB) | IkamusumeFan (talk | contribs) | Thicker lines for visibility. | ||
04:16, 21 July 2013 | 360 × 360 (86 KB) | IkamusumeFan (talk | contribs) | User created page with UploadWizard |
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Height | 288pt |