Examples of using Boxplot in English and their translations into Portuguese
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
Chart types: stock chart and boxplot.
The boxplot was a data plotting analysis tool used in the study.
The data were also used to configure a boxplot graph.
A Boxplot was built considering school material weight and presence of back pain.
To view the results obtained, boxplot graphs were used.
Figure 2- Boxplot illustrating the difference between the groups with and without cardiotoxicity.
These data are shown in Table 2,illustrative chart boxplot 4 format.
A boxplot graph was created between delta T and the patients' perception of a cardiac event.
The group medians anddistributions are illustrated in a boxplot graph in Fig.
Figure 2 Boxplot for the variable OB2014 on the continents Africa, the Americas, Asia, Europe, and Oceania.
Figure 1 shows the histogram of frequencies and the boxplot for the variable"proportion of obese adults in 2014.
For the boxplot, displaced values above zero were observed, indicating higher estimates for the LAF.
For the quantitative variables,we calculated some summary descriptive measurements and built boxplot type graphs.
Figure 1 Histogram and boxplot for the proportion of obese adults in 78 countries in 2014, respectively.
The estimates using the complex sampling design were made using simple linear regression,trend graphs and Boxplot.
Figure 2 shows the boxplot for the variable OB2014 on the continents Africa, America, Asia, Europe, and Oceania.
Figures 3 and 4 show the amplitude and latency values, of leads CZA2 and CZA1 of the MMN test of the entire sample N=30, according to the statistical analysis,by means of the Boxplot graph.
Boxplot of the comparison of the SMA flow volume in patients with CD in remission(group 1) and in activity group 2.
The qualitative variables were presented in terms of absolute and relative frequencies, andthe quantitative variables were presented using summary measurements and boxplot graphs.
Figure 1 Boxplot of the overall quality of life scores according to WHOQOL-1, WHOQOL-2 and quality of life/satisfaction groups.
Four instruments were used: a questionnaire, a card of data collection, a database and a teaching sequence contemplating ideas andcontent that aimed at developing understanding of statistical variability using the dotplot and boxplot.
The boxplot also shows that the highest median is in the rural population cases, as well as the highest dispersion, especially in 2007.
First, an analysis using the boxplot graphic was performed to determine if the units used in this work are homogeneous.
Boxplot graphs were elaborated with the distribution of BMI, according to the categories of SRH for men and women in each year considered.
The result of this test was illustrated with boxplot type charts, which schematically aggregates five measures: minimum value, first quartile, median second quartile, third quartile and maximum value.
Boxplot Figure 1 shows the variation of the daily NAS workload compared to the ideal NAS, calculated for the team available at work.
Boxplot proves the fact that all the sectors have an excessive workload as the daily NAS plots are above the ideal NAS ones.
The boxplot graphics depict respondent performance in subcategories I-A and I-B, category II and the Total-LAC according to age and SSD severity Figure 1.
Based on the boxplot analysis, a possible difference was observed in the proportions of obese adults in the Americas and Europe as compared to Africa and Asia.
The boxplot method for determining discrepant data was used because it is greatly used, easy to use and has great precision for detecting truly atypical observations.