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  1. www.statalist.org › general-stata-discussion › generalInterquartile range - Statalist

    28 Φεβ 2020 · I wanted to interpret my result by interquartile range (IQR), e.g., per one IQR. I have continuous predictor variable (x) and create this in stata: egen IQR1_x=iqr (x) gen IQR2_x=x/IQR1_x. then, I am going to use "IQR2_x" in my model and interpret as 'the change in the outcome var per one IQR change in the predictor (X).

  2. summarize— Summary statistics 3 Example 1: summarize with the separator() option We have data containing information on various automobiles, among which is the variable mpg, the mileage rating. We can obtain a quick summary of the mpg variable by typing. use https://www.stata-press.com/data/r18/auto2 (1978 automobile data). summarize mpg

  3. 11 Μαΐ 2021 · The interquartile range of a dataset, often abbreviated IQR, is the difference between the first quartile (the 25th percentile) and the third quartile (the 75th percentile) of the dataset. In simple terms, it measures the spread of the middle 50% of values. IQR = Q3 – Q1.

  4. 25 Σεπ 2020 · The interquartile range (IQR) contains the second and third quartiles, or the middle half of your data set. Whereas the range gives you the spread of the whole data set, the interquartile range gives you the range of the middle half of a data set.

  5. Quick start. Display the means of x1 and x2 grouped by chosen alternatives identified by depvar and using cmset data cmsummarize x1 x2, choice(depvar) Same as above, and display sample size, minimum, median, and maximum cmsummarize x1 x2, choice(depvar) statistics(N min median max)

  6. st: AW: interquartile range. Date. Tue, 17 Aug 2010 16:54:25 +0200. <>. You can use -egen, iqr()- if you want a variable to hold the result for you, or want it -by- a -varlist-, or use -tabstat-: *************. sysuse auto, clear. bys foreign: egen myiqr=iqr(price)

  7. The interquartile range is an interval, not a scalar. You should always report both numbers, not just the difference between them. You can then explain it by saying that half the sample readings were between these two values, a quarter were smaller than the lower quartile, and a quarter higher than the upper quartile.

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