L1 Real-Life Applications of Probability
Completion requirements
Unit E: Statistics and Probability
Chapter 2: Probability
Real-Life Applications of Probability
In baseball, one of the statistics given for players is their batting average. Batting average is a probability expressed as a decimal . A batting average of 0.286 means that of 1 000 times at bat, the player will hit the ball approximately 286 times.
«math xmlns=¨http://www.w3.org/1998/Math/MathML¨» «mfrac» «mn»286«/mn» «mrow» «mn»1«/mn» «mo»§#160;«/mo» «mn»000«/mn» «/mrow» «/mfrac» «mo»=«/mo» «mn»0«/mn» «mo».«/mo» «mn»286«/mn» «/math»
The higher the batting average, the more likely the player is to hit the ball when he or she is at bat.
«math xmlns=¨http://www.w3.org/1998/Math/MathML¨» «mfrac» «mn»286«/mn» «mrow» «mn»1«/mn» «mo»§#160;«/mo» «mn»000«/mn» «/mrow» «/mfrac» «mo»=«/mo» «mn»0«/mn» «mo».«/mo» «mn»286«/mn» «/math»
The higher the batting average, the more likely the player is to hit the ball when he or she is at bat.
The insurance business is very aware of probability when determining rates and premiums. New drivers and drivers under the age of 25 have a higher probability of getting in an accident than older, experienced drivers. As a result, new drivers and drivers
under the age of 25 have the highest insurance rates.
The probability of winning the lottery is very small. A person has a better chance of getting into a car accident, plane crash, or struck by lightning than winning the lottery.
For example, the probability to win the 649 jackpot is less than 1 in approximately 14 million.
«math xmlns=¨http://www.w3.org/1998/Math/MathML¨»«mfrac»«mn»1«/mn»«mrow»«mn»13«/mn»«mo»§#160;«/mo»«mn»983«/mn»«mo»§#160;«/mo»«mn»816«/mn»«/mrow»«/mfrac»«mo»§#215;«/mo»«mn»100«/mn»«mo»%«/mo»«mo»=«/mo»«mn»0«/mn»«mo».«/mo»«mn»000«/mn»«mo»§#160;«/mo»«mn»007«/mn»«mo»§#160;«/mo»«mn»2«/mn»«mo»%«/mo»«/math»
For example, the probability to win the 649 jackpot is less than 1 in approximately 14 million.
«math xmlns=¨http://www.w3.org/1998/Math/MathML¨»«mfrac»«mn»1«/mn»«mrow»«mn»13«/mn»«mo»§#160;«/mo»«mn»983«/mn»«mo»§#160;«/mo»«mn»816«/mn»«/mrow»«/mfrac»«mo»§#215;«/mo»«mn»100«/mn»«mo»%«/mo»«mo»=«/mo»«mn»0«/mn»«mo».«/mo»«mn»000«/mn»«mo»§#160;«/mo»«mn»007«/mn»«mo»§#160;«/mo»«mn»2«/mn»«mo»%«/mo»«/math»
Weather forecasting is an example of probability in daily life. To describe the chance of precipitation, meteorologists provide the POP, the probability of precipitation. The POP is written as a percent. The higher the POP, the more likely it
is to rain. If the POP is 80%, 90%, or 100%, it will most likely rain.
According to Environment Canada, POP is the chance that precipitation greater than 0.2 mm of rain or 0.2 cm of snow will fall during a certain period. The POP is included in a forecast only if it is above 30%. A 30% POP means that in 3 out of 10 days in which the meteorologist has seen the current environmental conditions, precipitation has occurred. A POP of 30% indicates a small chance of precipitation, while a POP of70% indicates a high chance.
According to Environment Canada, POP is the chance that precipitation greater than 0.2 mm of rain or 0.2 cm of snow will fall during a certain period. The POP is included in a forecast only if it is above 30%. A 30% POP means that in 3 out of 10 days in which the meteorologist has seen the current environmental conditions, precipitation has occurred. A POP of 30% indicates a small chance of precipitation, while a POP of70% indicates a high chance.
