**Problem Statement** Show that the Dirichlet function \( f \) defined on \([0, 1]\) by \[ f(x) = \begin{cases} 1 & \text{if } x \text{ is rational} \\ 0 & \text{if } x \text{ is irrational} \end{cases} \] is not Riemann integrable on \([0, 1]\). **Explanation** The Dirichlet function is an example of a function that is defined differently for rational and irrational numbers. It is 1 for any rational \( x \) and 0 for any irrational \( x \). This function serves as a classic example in analysis to illustrate properties related to integrability and discontinuity, especially in the context of Riemann integration. To show that it is not Riemann integrable, consider that for a function to be Riemann integrable, it must be continuous almost everywhere on the interval of integration. The Dirichlet function is discontinuous at every point in \([0, 1]\), as between any two rationals there exist irrationals and vice versa. Hence, it fails to meet the criteria for Riemann integrability.
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
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