# scipy.stats.chi2() | Python

scipy.stats.chi2() is an chi square continuous random variable that is defined with a standard format and some shape parameters to complete its specification.

Parameters :
q : lower and upper tail probability
x : quantiles
loc : [optional]location parameter. Default = 0
scale : [optional]scale parameter. Default = 1
size : [tuple of ints, optional] shape or random variates.
moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : chi squared continuous random variable

Code #1 : Creating chi squared continuous random variable

 `# importing scipy ` `from` `scipy.stats ``import` `chi2 ` ` `  `numargs ``=` `chi2.numargs ` `[a] ``=` `[``0.6``, ] ``*` `numargs ` `rv ``=` `chi2(a) ` ` `  `print` `(``"RV : \n"``, rv)  `

Output :

```RV :
<scipy.stats._distn_infrastructure.rv_frozen object at 0x0000029485196DD8>
```

Code #2 : chi2 random variates and probability distribution function.

 `import` `numpy as np ` `quantile ``=` `np.arange (``0.01``, ``1``, ``0.1``) ` `  `  `# Random Variates ` `R ``=` `chi2.rvs(a, scale ``=` `2``,  size ``=` `10``) ` `print` `(``"Random Variates : \n"``, R) ` ` `  `# PDF ` `R ``=` `chi2.pdf(a, quantile, loc ``=` `0``, scale ``=` `1``) ` `print` `(``"\nProbability Distribution : \n"``, R) `

Output :

```Random Variates :
[6.20115012e-01 4.82717678e-01 1.43760444e-02 1.19755537e+00
3.00093606e-05 6.11268950e-01 5.99940774e-01 3.20509994e-01
1.94220599e-01 6.63225404e-01]

Probability Distribution :
[0.00615404 0.06544849 0.12034254 0.1704933  0.21568622 0.25581903
0.29088625 0.32096438 0.34619796 0.36678666]
```

Code #3 : Graphical Representation.

 `import` `numpy as np ` `import` `matplotlib.pyplot as plt ` ` `  `distribution ``=` `np.linspace(``0``, np.minimum(rv.dist.b, ``5``)) ` `print``(``"Distribution : \n"``, distribution) ` ` `  `plot ``=` `plt.plot(distribution, rv.pdf(distribution)) `

Output :

```Distribution :
[0.         0.10204082 0.20408163 0.30612245 0.40816327 0.51020408
0.6122449  0.71428571 0.81632653 0.91836735 1.02040816 1.12244898
1.2244898  1.32653061 1.42857143 1.53061224 1.63265306 1.73469388
1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878
2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367
3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857
3.67346939 3.7755102  3.87755102 3.97959184 4.08163265 4.18367347
4.28571429 4.3877551  4.48979592 4.59183673 4.69387755 4.79591837
4.89795918 5.        ]```

Code #4 : Varying Positional Arguments

 `import` `matplotlib.pyplot as plt ` `import` `numpy as np ` ` `  `x ``=` `np.linspace(``0``, ``5``, ``100``) ` ` `  `# Varying positional arguments ` `y1 ``=` `chi2.pdf(x, ``1``, ``6``) ` `y2 ``=` `chi2.pdf(x, ``1``, ``4``) ` `plt.plot(x, y1, ``"*"``, x, y2, ``"r--"``) `

Output :

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