Question

Automobiles that are more than 10 years old must pass a vehicle inspection to be registered in a particular state. The state reports the probability that a car more than 10 years old will fail the vehicle inspection is \(0.09 .\) Give a relative frequency interpretation of this probability.

Short answer

The relative frequency interpretation of this probability is that out of every 100 cars that are 10 years or older, 9 are expected to fail the vehicle inspection.

Step-by-step solution

Understanding Probability

In this exercise, we are given that the probability of a car that is over 10 years old failing the vehicle inspection is \(0.09\). This means that if you randomly select a car that is more than 10 years old, there is a \(9%\) chance that the car will fail the vehicle inspection.

Relative Frequency Interpretation of Probability

The relative frequency of an event is calculated as the number of times that the event occurs divided by the total number of trials. In the context of this exercise, the 'event' is a car failing the inspection, and the 'total number of trials' would be the total number of cars over 10 years old. So, a relative frequency interpretation of this probability is 'Out of every 100 cars that are 10 years or older, 9 are expected to fail the vehicle inspection.'

Key concepts

Understanding Probability

When delving into the world of mathematics and statistics, the concept of probability often emerges as a fundamental element. Probability is the measure of how likely an event is to occur, and it is depicted as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

For example, the problem given highlights the probability of older vehicles failing an inspection, which is stated as 0.09. This figure expresses the likelihood of a particular event—in this case, the event being a vehicle older than 10 years failing an inspection. Understanding this probability is crucial for various stakeholders, such as vehicle owners, inspection agencies, and policy makers, because it helps in preparing for and managing expectations surrounding vehicle inspections.

To bring this concept closer to everyday situations, imagine having a bag of 100 marbles, with 9 marbles being red and the rest being blue. If you were to draw a marble without looking, you’d have a 9% chance of picking a red marble. This visual representation aligns with the introduction to probability as a measure of likelihood, paving the way for a more approachable connection to mathematical outcomes.

Relative Frequency

The term 'relative frequency' refers to the ratio representing how often an event occurs compared to the total number of trials or opportunities for it to occur. To calculate the relative frequency of an event, one must divide the number of times the event happens by the total number of observations or trials.

Continuing with our vehicle inspection example, the probability of 0.09 means that in a large enough sample, if we inspect 100 cars that are more than 10 years old, we would expect about 9 of those cars to fail the inspection, giving us a relative frequency of 9 failures per 100 inspections.

However, it is essential to note that relative frequency becomes more accurate with a larger number of trials. If only a few cars are inspected, the number of failures could fluctuate quite a bit. But as the number of inspected cars increases, the relative frequency of failures is more likely to approach the probability of 0.09. This conveys an essential principle in probability and statistics: the law of large numbers, which states that as more observations are collected, the actual ratio of outcomes will get closer to the theoretical probability.

Vehicle Inspection Probability

Focusing specifically on the scenario of vehicle inspection probability, it's a real-world example of how probability is utilized to predict or explain phenomena. As stated in the exercise, there is a 9% chance that a car over 10 years old will fail the inspection. This probability can guide decisions about when and how often to inspect vehicles and can also be used to set policies regarding vehicle maintenance and safety standards.

Understanding the vehicle inspection probability can help car owners gauge the likelihood that their vehicle might require repairs before passing inspection. It also has implications for regulatory bodies to ensure that cars on the road meet safety requirements, thus providing a safer driving experience for everyone.

Auto repair shops and manufacturers could also make use of this statistic. They might anticipate an increased demand for services or parts that frequently cause older cars to fail inspections, allowing them to better stock supplies and schedule staffing. In this case, understanding and interpreting probability proves to be a valuable tool in various operational and strategic decision-making processes tied to vehicle inspection.