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Q: Does this distribution whose five-number summary is shown below have at least one outlier 21.7 55.3 73.4 89.3 140.1?

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In a normal distribution half (50%) of the distribution falls below (to the left of) the mean.

correlation is drawn from all data points. if you look at the r^2 value and it's below 0.99 for example (should be higher in non research work (and in much research work) it indicates that 1 of your points may be an outlier. If you input all datapoints into excel, you may be able to see the point that's throwing it off. There are also statistical tests you can do to spot an outlier. In other words, correlation is not independent of an outlier. it will make the r^2 value worse. If the outlier is taken out, then the correlation could be deemed independent but only because you manipulated it and had taken the outlier out

It is not. It depends on what question you want to answer. They are both equally informative, but in different circumstances.the CRFD can be used to determine a summary of proportion of observations that lies above(or below) a particular value in a data set which the RFD cannot

The Poisson distribution with parameter np will be a good approximation for the binomial distribution with parameters n and p when n is large and p is small. For more details See related link below

The Poisson distribution is a discrete distribution, with random variable k, related to the number events. The discrete probability function (probability mass function) is given as: f(k; L) where L (lambda) is the mean and square root of lambda is the standard deviation, as given in the link below: http://en.wikipedia.org/wiki/Poisson_distribution

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The outlier

It is no ossible to answer the question because all the digits have been run together to form a single large number.

In a normal distribution half (50%) of the distribution falls below (to the left of) the mean.

According to Anderson, Sweeney Williams book Essential of Statistics For Business and Economics, 4e Edition, 2006 p. 34 cumulative frequency distribution is "a variation of the frequency distribution that provides another tabular summary of quantitative data." In simple terms, the cumulative frequency distribution is the sum of the frequencies of all points or outcomes below and including the current point.

In the normal distribution, the mean and median coincide, and 50% of the data are below the mean.

Link to the summary will be included in the related link below.

Clumped

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look below for a few examples of a summary a summary is also similar to the journal abstracts

correlation is drawn from all data points. if you look at the r^2 value and it's below 0.99 for example (should be higher in non research work (and in much research work) it indicates that 1 of your points may be an outlier. If you input all datapoints into excel, you may be able to see the point that's throwing it off. There are also statistical tests you can do to spot an outlier. In other words, correlation is not independent of an outlier. it will make the r^2 value worse. If the outlier is taken out, then the correlation could be deemed independent but only because you manipulated it and had taken the outlier out

It is not. It depends on what question you want to answer. They are both equally informative, but in different circumstances.the CRFD can be used to determine a summary of proportion of observations that lies above(or below) a particular value in a data set which the RFD cannot

For a summary of the life of St. Nicholas of Myra, click on the link below.

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