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.

If you are planning a survey project, please consider Creating Surveys on AMAZON

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

Links to Connections

My Page www.suttong.com

My Books AMAZON and GOOGLE STORE

FOLLOW FACEBOOK Geoff W. Sutton TWITTER @Geoff.W.Sutton

PINTEREST www.pinterest.com/GeoffWSutton

Articles: Academia Geoff W Sutton ResearchGate Geoffrey W Sutton

Personal Self-Concept Questionnaire (PSQ)

The Personal Self-Concept Questionnaire ( PSQ ) Overview The Personal Self-Concept Questionnaire (PSQ) measures self-concept based on ratings of 18 items, which are grouped into four categories: Self-fulfilment, autonomy, honesty, and emotional self-concept. Subscales : The PSQ has four subscales 1. Self-fulfilment (6 items) 2. Autonomy (4 items) 3. Honesty (3 items) 4. Emotional self-concept (5 items) 👉 [ Read more about Self-Concept and Self-Identity] The PSQ is a Likert-type scale with five response options ranging from totally disagree to totally agree. Reliability and Validity In the first study, coefficient alpha = .85 and in study two, alpha = .83. Data analysis supported a four-dimensional model (see the four categories above). Positive correlations with other self-concept measures were statistically significant. Other notes The authors estimated it took about 10 minutes to complete the PSQ. Their first study included people ages 12 to 36 ( n = 50...

Student Self-Efficacy

Assessment name: STUDENT SELF-EFFICACY SCALE * Note. This post has been updated to provide an available measure of student self-efficacy. ———- Scale overview: The student self-efficacy scale i s a 10-item measure of self-efficacy. It was developed using data from university nursing students in the United States. Authors: Melodie Rowbotham and Gerdamarie Schmitz Response Type: A four-choice rating scale as follows: 1 = not at all true 2 = hardly true 3 = moderately true 4 = exactly true Self-efficacy is the perception that a person can act in a way to achieve a desired goal. Scale items There are 10 items. Examples: I am confident in my ability to learn, even if I am having a bad day. If I try hard enough, I can obtain the academic goals I desire. Psychometric properties The authors reported that their sample scores ranged from 25 to 40 with a scale mean of 34.23 ( SD = 3.80. Internal consistency was high at alpha = .84. The a...

Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ)

Scale name: Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ) Scale overview: The Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ) is a 29-item self-report measure of both mathematics self-efficacy and mathematics anxiety. Author: Diana Kathleen May Response Type: Items are rated on a 5-point Likert-type scale following a “no response” option: 1 = Never 2 = Seldom 3 = Sometimes 4 = Often 5 = usually Sample items 1. I feel confident enough to ask questions in my mathematics class. 6. I worry that I will not be able to get a good grade in my mathematics course. Subscales and basic statistics for the MSEAQ Self-Efficacy M = 44.11, SD = 10.78, alpha = .93 Anxiety M = 46.47, SD = 12.61, alpha = .93 Total Scale M = 90.58, SD = 22.78, alpha = .96 Reliability: See the Cronbach’s alpha levels reported above. Validity: There were significant ...

Assessment, Statistics, and Research

Search This Blog