A study reported in a journal found that in a certain state retired male policemen are more likely to have heart disease compared to other men with similar ages but different occupations. Data from the study were that about 34% of a sample of 200 retired policemen had heart disease but only 17% of a sample of 800 men with other occupations had heart disease. (a) In Chapter 6, we learned about the various types of studies. Is this an observational study or a randomized experiment? Explain. This is a randomized experiment because the researchers simply observed the proportion with heart disease for both policemen and men of other occupations.This is an observational study because the researchers assigned certain men to be policemen or not. This is an observational study because the researchers simply observed the proportion with heart disease for both policemen and men of other occupations.This is a randomized experiment because the researchers assigned certain men to be policemen or not. (b) Do you think that we can attribute the observed difference in heart disease percentages to job-related factors? Explain c)Calculate a 95% confidence interval for the proportion of retired policemen in the state who have heart disease. (Round your answers to three decimal places.) __to___ d) Calculate a 95% confidence interval for the proportion of other retired men who have heart disease. (Round your answers to three decimal places.) ___to___
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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