Showing posts with label presenting percentages. Show all posts
Showing posts with label presenting percentages. Show all posts

Tuesday, July 28, 2020

Charting Dual Average Percentages as Linear Trends

An excellent example of presenting two sets of data from multiple sources over time can be found in the presentation of polling data on FiveThirtyEight.*

The point of  this post is to identify a useful way to present data from multiple sources over time.



The charts are continually updated as data from new polls are received*. The data for each of the two main candidates are plotted and a trend line shows the averages for each candidate. From left to right we see the progress based on the dates of each poll.

Notes about the chart and the data

1. Percentages can be averaged and yield a meaningful and easy way to interpret multiple sets of data.
2. The narrowing and widening of the trend lines offers a quick glance at what is happening for each candidate or data source.
3. Averaging polls from multiple sources helps avoid bias due to emphasizing preferred outcomes.
4. Below the chart are tables of data showing important information useful to research methods
   4.1 Dates are listed and are clearly important as events can change what happens.
   4.2 The data source is listed, which adds to confidence that we are not dealing with hidden data.
   4.3 The size of the sample is important to determine accuracy.
   4.4 The type of sample is important. So, LV = likely voters is more important to voting outcomes than is a general population sample. Other types of samples are listed.
   4.5 The results are listed along with the difference presented as a net result. On this day Biden was 8 points ahead of Trump.

It is worth noting in polls like this that events can change the trend. That is, just because Biden is consistently ahead of Trump does not mean this will be true later in the year. Also, it is important to remember that in the US, the popular vote does not determine who wins in a close election. As in 2016, the president won the electoral vote but lost the popular vote. Thus, polling based on electoral votes will be more useful for predicting election outcomes.

*Nate Silver is the founder of the website FiveThirtyEight. The story of Nate Silver's excellent predictions can be found in The Signal and the Noise: Why So Many Predictions Fail--but Some Don't

**Data Note that, in science writing, the word data takes a plural verb so, "data are" not "data is." To refer to a single unit of data, use the word datum. See dictionary.com In nonscience writing, data has been used as singular or plural.

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Cite this blog post

Sutton, G.W. (2020, July 28). Charting Dual Average Percentages as Linear Trends. Assessment, Statistics, & Research. https://statistics.suttong.com /2020/07/charting-dual-average-percentages-as.html



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Thursday, December 21, 2017

Presenting Survey Results








We can learn a lot about presenting survey results by looking at what experts do. The scientists at Pew Research presented findings from a Christmas in America survey. Take a look at their work.

1. Focus on highlights. For general audiences, select the most important facts. For example, it is no big news to say over 90% of Christian Americans celebrate Christmas. But to learn there’s a drop in celebrating Christmas as a religious rather than a cultural holiday is news (46% down from 51% in 2013). It’s also interesting to learn that younger persons are lower on the religious emphasis than are older adults. Of course, to focus on highlights, you have to create good survey questions in the first place. So, check out the items Pew reports to make their findings more meaningful (e.g., include age groups and religious affiliation in your survey).

2. Use percentages and graphics to depict trends. On fact 2, “Merry Christmas” or “Happy Holidays,” Pew shows a change in the trend for “it doesn’t matter” what people say in stores or businesses. Endorsing the phrase “It doesn’t matter” rose from 45% in 2005 to 52% in 2017. Percentages make sense to most educated readers. Means and standard deviations are not as widely understood. Simple line and bar graphs also help readers avoid losing focus in dense text. Again, see the Pew examples: Christmas in America survey.

3. Pew does a good job of presenting different answers to a complex question about Christian displays (e.g., Nativity scenes) on government property. Some think the displays should never be allowed (26%), others think its fine if there are other symbols (29%), while most think they should be allowed without other symbols (37%). By presenting years 2014 and 2017 on two different lines, we see how the views have changed. In addition, the report uses color to help us compare the different group responses.

4. Present controversial beliefs with enough detail to make it clear who believes what. Pew asked questions about the historicity of the Christmas story events—things like virgin birth and visitors guided by a star. The key words for each item are printed next to the data presented for two recent years (2014 and 2017). We see that belief in the virgin birth dropped from 73 to 66% from 2014 to 2017. You do have to read the text to learn that the findings are different among those in the sample who identify as Christian.


For those wanting more detail, Pew includes a link to their “Religion & Public Life” page. If you follow the link, you will see much more detail in the tables. The tables also provide another example of how to present data to a general audience.

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Belief in God Scale

  Assessment name: Belief in God Scale Scale overview: Authors: D. Randles et al. (2015). Response Type: Items are rated on a scale ...