# Regarding exercises from data science

Can anyone tell me how to solve exercise from week 19 ,first video.

`````` fig, axs = plt.subplots(3, 1)
num_samples = 1000
i = 0
for sample_size in [100, 1000, 10000]:
#dice throw, uniform, outcome: 1, 2, 3, 4, 5, 6

#Each element represent the face up on dice(R.V), sum along the columns will form the new R.V.
samples = np.random.randint(1, 6, (num_samples, sample_size))
x = samples.sum(axis=1)

#see if CLT holds.
axs[i].hist(x, bins=50)
i = i + 1``````

Here, is my solution

import numpy as np
import pandas as pd
import random
import matplotlib.pyplot as plt

``````#build Uniform distribution as the population, you can replace the uniform distribution by Binomial, Normal, etc.

s = np.random.uniform(0,1,1000000)
``````

# take sample from polulation

``````no_sample = [10,100,1000,10000]
mean_sampl = []
sampl_size = 250
for i in no_sample:
each_s_m = []
for j in range(0,i):
rc = random.choices(s, k=sampl_size)
each_s_m.append(sum(rc)/len(rc))
mean_sampl.append(each_s_m)
``````
``````#>  Plot the mean distribution
``````
``````cols = 2
rows = 2
fig, ax = plt.subplots(rows, cols, figsize=(20,15))
n = 0
for i in range(0, rows):
for j in range(0, cols):
ax[i, j].hist(mean_sampl[n], 200, density=True)
ax[i, j].set_title(label="number of sampling :" + str(no_sample[n]))
n += 1
plt.show()``````