NURS341 Lecture Notes - Lecture 5: Cumulative Frequency Analysis, Quartile, Reinforcement

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o Ex. values of the frequency distribution in figure 2-1 have been collected into 2
groups: (1) patients who spent 4 days or fewer in postop and 2) those who spent
5 days or more
o When data is grouped, some information is lost
o You can make intervals so large that they are meaningless
o Make sure ot to ake iterals too sall or o’t eefit oer a stadard
frequency distribution
Percentages
o Percentage part of the whole
o To calculate a percentage, divide the partial number of items by the total
number of items and then multiply by 100
o E. What peretage of our patiets do those  represet?
o Number of patients of interest is 18 (those discharged after day 4)
o Total number of patients studied is 50 (see last line of third column)
o First step is 18 divided 50, then get 0.36 then times by 100 then get 36%
o Cumulative percentage percentage of observations with a value less than the
maximum value of the variable interval (idea same as cumulative frequency)
Quantiles, Quartiles, Percentiles
o Quantiles is like dividing a data set into different portions or bins
o 2 special cases of quantiles are percentiles and quartiles
o Percentiles divide a data set into 100 equal portions
o If patiet’s BMI is i th percentile, then 90% of BMIs in reference population used to
deelop distriutio ere at or elo this patiet’s BMI (patiet’s BMI is i the top %
reference population)
o Quartiles divide a data set into 4 equal parts
o ex. Nursing manager wants to hire students finished in top quarter of the class on an
exam, she would calculate the third quartile and select all the scores above it
o Formula for calculating percentiles:
o P = (n+1) x y/100
- P = the number of observations at the percentile for which you are looking (Ex. 166
nurses at the 50th percentile saw 16 patients)
o n = the number of observations in your data set
o Y = the peretile ou’re lookig for
Apply this formula to find the median or middle observation:
o P = (331 + 1) x 50/100 = 166
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Document Summary

Ex. values of the frequency distribution in figure 2-1 have been collected into 2 groups: (1) patients who spent 4 days or fewer in postop and 2) those who spent. 5 days or more: when data is grouped, some information is lost, you can make intervals so large that they are meaningless, make sure (cid:374)ot to (cid:373)ake i(cid:374)ter(cid:448)als too s(cid:373)all or (cid:449)o(cid:374)"t (cid:271)e(cid:374)efit o(cid:448)er a sta(cid:374)dard frequency distribution. Quantiles, quartiles, percentiles: quantiles is like dividing a data set into different portions or bins, 2 special cases of quantiles are percentiles and quartiles, percentiles divide a data set into 100 equal portions. Nursing manager wants to hire students finished in top quarter of the class on an exam, she would calculate the third quartile and select all the scores above it: formula for calculating percentiles, p = (n+1) x y/100. P = the number of observations at the percentile for which you are looking (ex.

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