Subject Area : Number of Pages : Type of Document : Spacing : Style : Academic Level : Preferred Language : Assignment Description:Complete Exercises 6, 8, and 9 in Statistics for Nursing Research: A Workbook for Evidence-Based Practice, and submit as directed by the instructor.]
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Complete Exercises 6, 8, and 9 in Statistics for Nursing Research: A Workbook for Evidence-Based Practice, and submit as directed by the instructor.]
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chapter 6
Understanding Frequencies
and Percentages
STATISTICAL TECHNIQUE IN REVIEW
Frequency is the number of times a score or value for a variable occurs in a set of data.
Frequency distribution is a statistical procedure that involves listing all the possible
values or scores for a variable in a study. Frequency distributions are used to organize
study data for a detailed examination to help determine the presence of errors in coding
or computer programming ( Grove, Burns, & Gray, 2013 ). In addition, frequencies and
percentages are used to describe demographic and study variables measured at the nominal
or ordinal levels.
Percentage can be defi ned as a portion or part of the whole or a named amount in
every hundred measures. For example, a sample of 100 subjects might include 40 females
and 60 males. In this example, the whole is the sample of 100 subjects, and gender is
described as including two parts, 40 females and 60 males. A percentage is calculated
by dividing the smaller number, which would be a part of the whole, by the larger
number, which represents the whole. The result of this calculation is then multiplied
by 100%. For example, if 14 nurses out of a total of 62 are working on a given day, you
can divide 14 by 62 and multiply by 100% to calculate the percentage of nurses working
that day. Calculations: (14 ÷ 62) × 100% = 0.2258 × 100% = 22.58% = 22.6%. The answer
also might be expressed as a whole percentage, which would be 23% in this example.
A cumulative percentage distribution involves the summing of percentages from the
top of a table to the bottom. Therefore the bottom category has a cumulative percentage
of 100% (Grove, Gray, & Burns, 2015). Cumulative percentages can also be used to determine
percentile ranks, especially when discussing standardized scores. For example, if 75%
of a group scored equal to or lower than a particular examinee s score, then that examinee s
rank is at the 75 th percentile. When reported as a percentile rank, the percentage is often
rounded to the nearest whole number. Percentile ranks can be used to analyze ordinal
data that can be assigned to categories that can be ranked. Percentile ranks and cumulative
percentages might also be used in any frequency distribution where subjects have only one
value for a variable. For example, demographic characteristics are usually reported with the
frequency ( f ) or number ( n ) of subjects and percentage (%) of subjects for each level of a
demographic variable. Income level is presented as an example for 200 subjects:
Income Level Frequency ( f ) Percentage (%) Cumulative %
1. < $40,000 20 10% 10% 2. $40,000$59,999 50 25% 35% 3. $60,000$79,999 80 40% 75% 4. $80,000$100,000 40 20% 95% 5. > $100,000 10 5% 100%
EXERCISE
6
60 EXERCISE 6 Understanding Frequencies and Percentages
Copyright © 2017, Elsevier Inc. All rights reserved.
In data analysis, percentage distributions can be used to compare fi ndings from different
studies that have different sample sizes, and these distributions are usually arranged in
tables in order either from greatest to least or least to greatest percentages ( Plichta &
Kelvin, 2013 ).
RESEARCH ARTICLE
Source
