SciPy - Constants and Special Functions
You want to calculate the cumulative probability for values in a dataset assuming a normal distribution with mean 0 and variance 0.5. Which code correctly uses
erf to compute this?You want to calculate the cumulative probability for values in a dataset assuming a normal distribution with mean 0 and variance 0.5. Which code correctly uses erf to compute this?
hard📝 Application Q8 of 15
Step-by-Step Solution
Solution:
Step 1: Recall normal CDF formula using erf
The CDF for normal distribution is 0.5 * (1 + erf(x / (sqrt(2) * sigma))).Step 2: Apply variance to standard deviation
Standard deviation sigma = sqrt(variance) = sqrt(0.5).Step 3: Check code correctness
from scipy.special import erf import numpy as np data = np.array([0, 0.5, 1]) cdf = 0.5 * (1 + erf(data / np.sqrt(2 * 0.5))) correctly divides data by sqrt(2 * 0.5) and applies formula.Final Answer:
from scipy.special import erf\nimport numpy as np\ndata = np.array([0, 0.5, 1])\ncdf = 0.5 * (1 + erf(data / np.sqrt(2 * 0.5))) -> Option BQuick Check:
Normal CDF formula with erf applied correctly [OK]
Quick Trick: Normal CDF = 0.5*(1+erf(x/(sqrt(2)*sigma))) [OK]
Common Mistakes:
MISTAKES- Ignoring variance in denominator
- Using erf without scaling input
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