By Lance A Leventhal

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If the probabilities were known, we don't have to worry about statistical analysis. In simple terms, if we know the probabilities of the Satisfaction_Rating RV, we can simply use it to conclude whether more customers give Very Good rating against Poor. However, our survey data does not contain every customer who have availed car service from the workshop, and as such we have representative probabilities and not actual probabilities. Now, we have seen 20 observations in the R session, and corresponding to each row we had some values under the Satisfaction_Rating column.

It might appear at the outset that this is not a very useful random variable. However, the reader is cautioned that this intuition is not correct. As a simple case, this variable arises in many cases where simple random sampling is needed in action. com. com/support and register to have the files e-mailed directly to you. Figure 4: Probability distribution of a discrete uniform random variable Note The R programs here are indicative and it is not absolutely necessary that you follow them here. The R programs will actually begin from the next chapter and your flow won't be affected if you do not understand certain aspects of them.

0 and R will do the required remaining part of installing the package. One of the drawbacks of doing this process manually is that if there are dependencies, the user needs to ensure that all such packages have been installed before embarking on this second task of installing the R packages. However, despite the problem, it is quite useful to know this technique, as we may not be connected to Internet all the time and install the packages as it is convenient. RSADBE – the book's R package The book uses a lot of datasets from the Web, statistical text books, and so on.

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