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Apprendre Calculate Fascinating Probability | Discrete Distributions
Probability Theory
course content

Contenu du cours

Probability Theory

Probability Theory

1. Learn Basic Rules
2. Probabilities of Several Events
3. Conducting Fascinating Experiments
4. Discrete Distributions
5. Normal Distribution

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Calculate Fascinating Probability

Have you ever wonder that your friends birthday could be any day of the year with equal probability. The probability for each day creates uniform distribution.

Let's recall some functions, but for the uniform distribution (they are a little bit different): For calculating the probability of receiving exactly defined output x :

uniform.pdf(x, loc, scale).

For calculating the probability of receiving output that is bigger than x:

uniform.sf(x, loc, scale)(inclusive).

For calculating the probability of receiving output that is less than x:

uniform.cdf(x, loc, scale)(inclusive).

  • loc is the lower bound of the distribution (minimum value).
  • scale is the upper bound of the distribution (maximum value).
Tâche

Swipe to start coding

Imagine that you met a person and want to calculate the probability of his birthday in summer, you know he wasn't born on a leap year. So, follow the algorithm:

  1. Import uniform object.
  2. Calculate the probability that he was born after the 152nd day of the year (the 1st of June). With the parameters:
    • The lower bound is 1.
    • The upper bound is 365.
  3. Calculate the probability that he was born before the 243rd day of the year (the 31st of August). With the parameters:
    • The lower bound is 1.
    • The upper bound is 365.
  4. Calculate the probability that he was born before the 243rd day of the year and after the 152nd day of the year.

Solution

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Section 4. Chapitre 2
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book
Calculate Fascinating Probability

Have you ever wonder that your friends birthday could be any day of the year with equal probability. The probability for each day creates uniform distribution.

Let's recall some functions, but for the uniform distribution (they are a little bit different): For calculating the probability of receiving exactly defined output x :

uniform.pdf(x, loc, scale).

For calculating the probability of receiving output that is bigger than x:

uniform.sf(x, loc, scale)(inclusive).

For calculating the probability of receiving output that is less than x:

uniform.cdf(x, loc, scale)(inclusive).

  • loc is the lower bound of the distribution (minimum value).
  • scale is the upper bound of the distribution (maximum value).
Tâche

Swipe to start coding

Imagine that you met a person and want to calculate the probability of his birthday in summer, you know he wasn't born on a leap year. So, follow the algorithm:

  1. Import uniform object.
  2. Calculate the probability that he was born after the 152nd day of the year (the 1st of June). With the parameters:
    • The lower bound is 1.
    • The upper bound is 365.
  3. Calculate the probability that he was born before the 243rd day of the year (the 31st of August). With the parameters:
    • The lower bound is 1.
    • The upper bound is 365.
  4. Calculate the probability that he was born before the 243rd day of the year and after the 152nd day of the year.

Solution

Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 4. Chapitre 2
Switch to desktopPassez à un bureau pour une pratique réelleContinuez d'où vous êtes en utilisant l'une des options ci-dessous
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