```python
import matplotlib.pyplot as plt
import scipy.stats as st
import seaborn as sns
import pandas as pd
from scipy.stats import norm, uniform, expon
from scipy.integrate import quad
from sympy.solvers import solve
from sympy import Symbol
import numpy as np
from pandas import Series, DataFrame
```


```python
methodeA = Series([79.98, 80.04, 80.02, 80.04, 80.03, 80.03, 80.04,
79.97, 80.05, 80.03, 80.02, 80.00, 80.02])
print(methodeA.mean())
print(methodeA.std())
```

    80.02076923076923
    0.023965787580611863



```python
from scipy.stats import norm
np.random.seed(1)
methodeA_sim1 = Series(np.round(norm.rvs(size=6, loc=80, scale=0.02), 2))
methodeA_sim1
print(methodeA_sim1.mean())
print(methodeA_sim1.std())
```

    79.99333333333333
    0.028751811537128993



```python
np.random.seed(17)
for i in range(5):
    methodeA_sim1 = Series(np.round(norm.rvs(size=6, loc=80, scale=0.02), 2))
    print("Mittelwert:", np.round(methodeA_sim1.mean(), 3))
    print("Standardabw.:", np.round(methodeA_sim1.std(), 3))
    print()
```

    Mittelwert: 80.01
    Standardabw.: 0.027
    
    Mittelwert: 80.007
    Standardabw.: 0.02
    
    Mittelwert: 79.992
    Standardabw.: 0.028
    
    Mittelwert: 79.995
    Standardabw.: 0.016
    
    Mittelwert: 79.992
    Standardabw.: 0.013
    



```python
np.random.seed(463137)
methodeA_sim2 = Series(np.round(norm.rvs(size=6, loc=80, scale=0.02), 2))
methodeA_sim2
print(methodeA_sim2.mean())
print(methodeA_sim2.std())
```

    80.04
    0.019999999999998862



```python
np.random.seed(647)
methodeA_sim3 = Series(np.round(norm.rvs(size=13, loc=80, scale= 0.02), 2))
methodeA_sim3
print(methodeA_sim3.mean())
print(methodeA_sim3.std())
```

    79.99307692307691
    0.023588350014576355



```python
norm.cdf(x=499.57, loc=500, scale=1/np.sqrt(100))
```




    8.539905470989153e-06




```python
norm.cdf(x=171.54, loc=180, scale=10/np.sqrt(2))*100
```




    11.576543872967077




```python

```

391ef204612976d9524ddfb0f4b9138d9f184f6e
ipynb
Jupyter Notebook
Lernphase/SW06/.ipynb_checkpoints/Skript-checkpoint.ipynb
florianbaer/STAT
7cb86406ed99b88055c92c1913b46e8995835cbb
MIT
Lernphase/SW06/.ipynb_checkpoints/Skript-checkpoint.ipynb
florianbaer/STAT
7cb86406ed99b88055c92c1913b46e8995835cbb
MIT
Lernphase/SW06/.ipynb_checkpoints/Skript-checkpoint.ipynb
florianbaer/STAT
7cb86406ed99b88055c92c1913b46e8995835cbb
MIT
Qwen/Qwen-72B
1. YES
2. YES