Interpreting Box Plots with Questionnaire Data

In summary, the speaker is requesting help with interpreting box plots for questionnaire data with values ranging from 0 to 10. They are confused about the meaning of the median falling outside the box and having only upper or lower whiskers. They are also wondering if this indicates duplicated data values.
  • #1
jophysics
15
0
Dear all,
I need to evaluate some data from questionnaires (in the form of scale of values from 0 to 10) and I thought to use the box plots. Please, someone can provide me with some helps (references,etc) for the interpretation? In some cases, the median does not falls inside the box but it is the upper bound of the box, in other cases I have upper or lower wiskers only. What do these mean?

thank you for your help!

jo
 
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  • #2
If the median is the upper or lower end of a box then the median equals the lower or upper quartile. If you have only a whisker (say the upper whisker) than almost all of the measurements equal the upper quartile and you have one (or more?) values at the maximum.

In short, in both situations, you have good numbers of duplicated data values.
 

1. What is a box plot and how is it used to interpret questionnaire data?

A box plot, also known as a box and whisker plot, is a graphical representation of numerical data that summarizes the distribution of a set of values. It displays the five-number summary of a dataset, which includes the minimum, first quartile, median, third quartile, and maximum values. Box plots are useful for interpreting questionnaire data because they provide a visual representation of the distribution of responses and can help identify outliers or extreme values.

2. How do you create a box plot for questionnaire data?

To create a box plot for questionnaire data, you first need to organize the data into numerical values. Then, calculate the five-number summary of the dataset. Next, draw a horizontal line to represent the minimum and maximum values. Then, draw a box from the first quartile to the third quartile, with a line at the median. Finally, draw lines or "whiskers" from the box to the minimum and maximum values, and mark any outliers or extreme values beyond the whiskers.

3. How do you interpret the different components of a box plot?

The box in a box plot represents the middle 50% of the data, with the bottom of the box representing the first quartile and the top of the box representing the third quartile. The line in the middle of the box is the median, or the middle value of the dataset. The whiskers represent the range of the data, with the minimum and maximum values marked as dots. Outliers or extreme values are marked as individual points beyond the whiskers.

4. Can a box plot be used to compare multiple sets of questionnaire data?

Yes, box plots can be used to compare multiple sets of questionnaire data. By creating side-by-side box plots, you can easily compare the distribution of responses for different groups or categories. For example, you can compare the responses of males and females on a specific question or compare the responses of different age groups.

5. Are there any limitations to using box plots to interpret questionnaire data?

While box plots are useful for summarizing and interpreting questionnaire data, they do have some limitations. For example, they do not show the exact distribution of the data and may not be suitable for datasets with a small number of responses. Additionally, they may not be as effective for comparing large datasets or datasets with varying sample sizes. It is important to also consider other visualizations and statistical analyses when interpreting questionnaire data.

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