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Probability Theory

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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).

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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.

Lösning

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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).

Uppgift

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.

Lösning

Switch to desktopByt till skrivbordet för praktisk övningFortsätt där du är med ett av alternativen nedan
Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

close

Awesome!

Completion rate improved to 3.7

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