Skip to main content

Charting Troubles and Covid-19




How will we know if opening up the country is safe?

My bottom line answer is when people stop dying from Covid-19.

But tracking actual deaths can help us know whether we are making progress or not.

We can measure progress against our own baseline. The chart provides an estimate of a baseline, which will need to be corrected when additional deaths are recorded.

Think of the baseline as a channel.

The national US baseline appears to be in the range of 1800 to 2000 with some outliers starting 8 April 2020. I am not using averages because the data are not obviously normalized. I prefer to look at a range of relatively stable values, which can be called a channel. The sharp deviations have to be ignored to get a sense of what is "typical" of a pattern. A new relatively stable range above or below this range should help us determine a new trend. If the numbers are corrected, we will need to revisit the range. I am looking at a move of about 20% either way for evidence of a new range.

Local baselines will be more informative.

I admit, that the suffering for many with Covid-19 looks terrible even when they survive. But there seems to be quite a variation in discomfort of survivors from near death pain and distress to "I didn't know I was infected."

Problem Charts- So Many Ways to Tell a Story

I am fed up with charts showing invalid comparisons, wildly hypothetical projections, and tables incorrectly comparing Covid-19 to other conditions.

But when I tried to grab the raw data and focus on how many of our fellow Americans actually died, I realized that even these data are estimates as you can see from the spikes representing people found on a certain day that had not been counted.

So, after the rapid ramp up, in March we see a rough baseline between 1800 and 2000 deaths per day between 8 April and yesterday, 20 April.

The arithmetic mean is not helpful given the outliers. The data are not normal so far, so forget standard deviations.

The curves referred to by scientists and repeated by news readers are not yet evident. There is a part of the data that curves upward until around April 6 or so.

Death is a lagging indicator as some have said. This makes obvious sense because we do not know if an infected person will survive or not.

Some charts extend lines into the future. That only makes sense if we have accurate past data and if the data we have establish a pattern.

Flatten the curve only makes sense if there is a curve. I would prefer "create a plunge" meaning that there is a plateau and we want to get down near zero in as straight a line as possible.

Some use log charts- I am not a fan when we do not know the trend.

Some charts plot moving averages. That's a good idea--as long as you understand the concept and use the best averaging method. For example, are you going to average 3-day, 5-days, or what?

Testing

Testing is important personally and locally but the national numbers are too iffy because we do not know how many people are tested with what type of test and the level of accuracy of such tests. (Tests are not perfect.)

Testing is most valuable to isolate infected people from loved ones, co-workers, and others. Testing will be even more helpful when there is treatment for the condition.

Testing can help identify "hot spots" needing immediate resources like a nursing home or workplace.

I support testing. But charts of confirmed cases are not useful until an entire population is tested.

And testing with different tests having different levels of accuracy interfere with making other than rough judgments.

Media Folk Science

I'd like to suggest quarantining so many social media posts but that's not going to happen. Best wishes on learning statistics and charts. It really can help you make wise decisions for your personal life as well as in schools and workplaces.

Check the data

Important note: The numbers may be revised. This chart is for educational purposes only and not for planning.

Here is my source for the data  https://ourworldindata.org/grapher/total-daily-covid-deaths

p.s. Data is a plural noun. Say and write "data are" NOT "data is."

1-Apr 909
2-Apr 1059
3-Apr 915
4-Apr 1104
5-Apr 1344
6-Apr 1146
7-Apr 1342
------
8-Apr
------
1906
9-Apr 1922
10-Apr 1873
11-Apr 2087
12-Apr 1831
13-Apr 1500
14-Apr 1541
15-Apr 2408
16-Apr 4928
17-Apr 2299
18-Apr 3770
19-Apr 1856
20-Apr 1772
21-Apr 1857

Added data not in the chart

              22-Apr                    2524
              23-Apr                    1721
              24-Apr                    3179    Median April 8-24 = 1906
              25-Apr                    1054
              26-Apr                    2172
              27-Apr                    1687


Read more about statistics in these two books.


Creating Surveys on AMAZON















Read more about basic statistics in APPLIED STATISTICS: CONCEPTS FOR COUNSELORS at

AMAZON














Connections

My Page    www.suttong.com
  
My Books  AMAZON                       GOOGLE STORE

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

Publications (many free downloads)
 
Academia   Geoff W Sutton   (PhD)     

  ResearchGate   Geoffrey W Sutton   (PhD)






Comments

Popular posts from this blog

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)  ðŸ‘‰ [ 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 ...