Term
standard deviation (sigma, σ) |
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Definition
In statistics and probability theory, standard deviation (represented by the symbol sigma, σ) shows how much variation or "dispersion" exists from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. Also square root of the variance. |
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the average of all your sample |
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the middle most number of your sample given in value order if stretched out in a line. If you have an EVEN amount you add the middle pair of numbers and divide by 2. |
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putting the numbers in value order, mode is the number with the highest frequency (occurrence). You can also have bimodal (having two different modes) or multimodal (having multiple modes) |
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the averages of the squared differences from the mean. take each difference from the mean, square the result and divide total over total sample size (averaging the result). it is a measure of how far a set of numbers is spread out. |
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IQR = Q3-Q1 = 75% percentile - 25% percentile. First find the median of sample set. Next find Q1 or lower half of the number set, find the median of that set, that is Q1 or 25% of the spread of numbers. The set to the right of the median is the uppper half, find the median of that set and you have Q3 or the 75% of the number spread. See also In some texts, the interquartile range is defined differently. It is defined as the difference between the largest and smallest values in the middle 50% of a set of data. |
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Definition
Assume that the elements in a data set are rank ordered from the smallest to the largest. The values that divide a rank-ordered set of elements into 100 equal parts are called percentiles
An element having a percentile rank of Pi would have a greater value than i percent of all the elements in the set. Thus, the observation at the 50th percentile would be denoted P50, and it would be greater than 50 percent of the observations in the set. An observation at the 50th percentile would correspond to the median value in the set.
Quartiles divide a rank-ordered data set into four equal parts. The values that divide each part are called the first, second, and third quartiles; and they are denoted by Q1, Q2, and Q3, respectively.
Q1 is the "middle" value in the first half of the rank-ordered data set. Q2 is the median value in the set. Q3 is the "middle" value in the second half of the rank-ordered data set. |
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Term
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Definition
Assume that the elements in a data set are rank ordered from the smallest to the largest. The values that divide a rank-ordered set of elements into 100 equal parts are called percentiles
An element having a percentile rank of Pi would have a greater value than i percent of all the elements in the set. Thus, the observation at the 50th percentile would be denoted P50, and it would be greater than 50 percent of the observations in the set. An observation at the 50th percentile would correspond to the median value in the set. |
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Term
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Definition
Assume that the elements in a data set are rank ordered from the smallest to the largest. The values that divide a rank-ordered set of elements into 100 equal parts are called percentiles
An element having a percentile rank of Pi would have a greater value than i percent of all the elements in the set. Thus, the observation at the 50th percentile would be denoted P50, and it would be greater than 50 percent of the observations in the set. An observation at the 50th percentile would correspond to the median value in the set. |
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