Document1 - Word O Search Layout References Mailings Review View Help Suppose twenty-two communities have an average of 121.3 reported cases of larceny per year. Assume that o is known to be 37.3 cases per year. Find an 85%, 90%, and 95% confidence interval for the population mean annual number of reported larceny cases in such communities. Compare the margins of error. As the confidence level increase, do the margins of error increase? Question 2 options: The 85% confidence level has a margin of error of 53.7; the 90% confidence level has a margin of error of 61.4; and the 95% confidence level has a margin of error of 73.1. As the confidence level increases, the margins of error increase. The 85% confidence level has a margin of error of 11.5; the 90% confidence level has a margin of error of 13.1; and the 95% confidence level has a margin of error of 15.6. As the confidence level increases, the margins of error increase. The 85% confidence level has a margin of error of 2.4; the 90% confidence level has a margin of error of 2.8; and the 95% confidence level has a margin of error of 3.3. As the confidence level increases, the margins of error increase. The 85% confidence level has a margin of error of 15.6; the 90% confidence level has a margin of error of 13.1; and the 95% confidence level has a margin of error of 11.5. As the confidence level increases, the margins of error decrease.
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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