Probability Properties

Next wewill see some properties that we often encounter when solving probability questions:

  • When we have a probability composed of several possible outcomes the various probabilities must be summed to obtain the final probability.
  • The sum total of the probabilities in any trial is 1 1 , i.e., the probability of a certain outcome plus the probability of not having a certain outcome is equal to 1 1

Let us demonstrate this with two examples

Example 1

A die is rolled with 6 6 faces numbered from 1 1 to 6 6 .

The question is about the probability of an even number greater than 3 3 when rolling a die.

Looking at the data we have, we see that the two numbers that fit these criteria are 4 4 and 6 6 because they are even and greater than 3 3 . The probability that 4 4 will be rolled is . The probability that 6 6 will come up when rolling the die is also 16 \frac{1}{6}

Having said this, we must add both probabilities as follows and obtain 16+16=26=13 \frac{1}{6}+\frac{1}{6}=\frac{2}{6}=\frac{1}{3}

That is, the probability of rolling an even number greater than 3 3 when rolling a die is 13 \frac{1}{3}


Example 2

The forecast has stated that the probability of snow tomorrow is 30 30% .

From the above it follows that the probability of no snow tomorrow is 70 70% .

We should see that the sum of the probabilities of the forecast with or without snow is 1 1 .

Let us return to our data.

The probability of snow tomorrow is 30100=310 \frac{30}{100}=\frac{3}{10}

The probability of no snow tomorrow is 70100=710 \frac{70}{100}=\frac{7}{10}

From this it follows that the sum total of the probabilities is 310+710=1010=1 \frac{3}{10}+\frac{7}{10}=\frac{10}{10}=1


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