Uniform distribution in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the uniform distribution from scipy.stats.

SciPy

from scipy.stats import [1]

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Anorm

Bbinom

Cuniform

Dpoisson

Attempts:

3 left

💡 Hint

Common Mistakes

Importing a different distribution like norm or binom instead of uniform.

The uniform distribution is imported from scipy.stats using from scipy.stats import uniform.

2fill in blank

medium

Complete the code to create a uniform distribution object with lower bound 0 and upper bound 10.

SciPy

dist = uniform(loc=0, scale=[1])

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A10

B5

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using the upper bound directly as scale without subtracting lower bound.

Setting scale to 0 or 1 incorrectly.

The scale parameter is the width of the uniform distribution interval. For bounds 0 to 10, scale is 10.

3fill in blank

hard

Fix the error in the code to calculate the probability density function (PDF) at x=5 for the uniform distribution.

SciPy

pdf_value = dist.[1](5)

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Acdf

Bppf

Cpmf

Dpdf

Attempts:

3 left

💡 Hint

Common Mistakes

Using pmf which is for discrete distributions.

Using cdf instead of pdf.

The PDF (probability density function) is calculated using the pdf method for continuous distributions like uniform.

4fill in blank

hard

Fill both blanks to create a dictionary of probabilities for values 2 and 8 using the PDF method.

SciPy

probabilities = {2: dist.[1](2), 8: dist.[2](8)}

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Apdf

Bcdf

Cpmf

Dppf

Attempts:

3 left

💡 Hint

Common Mistakes

Using different methods for each value.

Using PMF or CDF instead of PDF.

Use the pdf method to get the probability density at specific points for a uniform distribution.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each number in the list to its PDF value if the number is greater than 3.

SciPy

result = {num: dist.[1](num) for num in numbers if num [2] 3 and num [3] 10}

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Apdf

B>

C<

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong comparison operators.

Using PMF or CDF instead of PDF.

The dictionary comprehension uses pdf to get probabilities. The condition filters numbers greater than 3 and less than 10.