Studies originating in France about 15 years ago claimed that moderate red wine drinking (1-2 glasses per day) lowered rates of heart disease. a). What would be an ideal way to test this theory? What data would you collect, on how many people and from where?b). If you were forced to use observational data from some big data sets, what would your dependent (Y) and independent (X) variables be?c). Can you imagine any sampling or measurement problems inherent to your study? How might they hinder your analysis?d). Could red wine be a confounding variable for something else, explain?e). Let’s suppose that you found with more than 99% confidence
Compound Probability
Compound probability can be defined as the probability of the two events which are independent. It can be defined as the multiplication of the probability of two events that are not dependent.
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Probability theory is a branch of mathematics that deals with the subject of probability. Although there are many different concepts of probability, probability theory expresses the definition mathematically through a series of axioms. Usually, these axioms express probability in terms of a probability space, which assigns a measure with values ranging from 0 to 1 to a set of outcomes known as the sample space. An event is a subset of these outcomes that is described.
Conditional Probability
By definition, the term probability is expressed as a part of mathematics where the chance of an event that may either occur or not is evaluated and expressed in numerical terms. The range of the value within which probability can be expressed is between 0 and 1. The higher the chance of an event occurring, the closer is its value to be 1. If the probability of an event is 1, it means that the event will happen under all considered circumstances. Similarly, if the probability is exactly 0, then no matter the situation, the event will never occur.
Studies originating in France about 15 years ago claimed that moderate red wine drinking (1-2 glasses per day) lowered rates of heart disease. a). What would be an ideal way to test this theory? What data would you collect, on how many people and from where?b). If you were forced to use observational data from some big data sets, what would your dependent (Y) and independent (X) variables be?c). Can you imagine any sampling or measurement problems inherent to your study? How might they hinder your analysis?d). Could red wine be a confounding variable for something else, explain?e). Let’s suppose that you found with more than 99% confidence that red wine reduced heart disease in France and the effect was substantial. Explain how the concepts of external validity and extrapolationmight or might not be concerns in applying the results to different groups in the United States?
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