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How do you find the harmonic and geometric mean for grouped data?
The geometric-harmonic mean of grouped data can be formed as a sequence defined as g(n+1) = square root(g(n)*h(n)) and h(n+1) = (2/((1/g(n)) + (1/h(n)))). Essentially, this means both sequences will converge to the mean, which is the geometric harmonic mean.
What are the disadvantages of using a histogram?
Advantages and Disadvantages of HistogramAdvantages:1) Visually strong.2) Can compare to normal curve.3) Usually vertical axis is a frequency count of items falling into each category.Disadvantages:1) Cannot read exact values because data is grouped into categories.2) More difficult to compare two data sets.3) Use only with continuous data.
How can you find the mean of grouped data?
finding grouped mean: you normally have a table like this : VISITS FREQ SUM
How do you find the quartiles of a data set?
First arrange the data set in ascending order. Suppose the data set consists of n observations. the index for the lower quartile is (n + 1)/4 and the index for the upper quartile is 3*(n + 1)/4. Find the values that correspond to the number in these positions in the ordered list. For example, if n = 15, then lower index = 4 and upper index = 12. So the lower quartile is the fourth number and the upper quartile is the twelfth. If n is large, you may skip the +1 and just look at n/4 and 3n/4. Often the indices are not integers. Then, if you are a beginner (nd the fact that you asked this question suggests that you are), find the nearest whole numbers for the two indices. Otherwise you need to interpolate and that is a whole new ball game!
How do you convert ordered data to nominal data?
I think you mean ordinal data. Similar to the golf tournament, you need to determine where to "cut" (from the ordinal data) so as to divide the data into different categories (to the nominal data). For example, if the ordinal data range from 1 to 6 (where 1 = the best) and the cut is 3, then you convert all the numbers from 1 to 3 to "1" (which represents "good") and the all numbers from 4 to 6 to "2" (which represents "bad"). In other words, 1, 2, and 3 from the original ordinal data set are converted to "1" (ordinal data); whereas 4, 5, and 6 from the original date set now become "2" (ordinal data). Eddie T.C. Lam
