Tuesday, May 26, 2020

Declines in weekly US Deaths on latest chart





If the posted data are accurate, we have an evident decrease on weekly deaths for the 7-days ending May 22 2020, which is the far right column. That is two weeks of decline and much lower than the April 18 column.

The bad news is of course that the US has reached 100,000 deaths.


Legend

M21 to A25 and M1 represent the Month and Day. The numbers below the dates are for the 7-days including the date. For example, M1 = 11,989 deaths in the 7-days before and including May 1, 2020. The first M dates are for March, then A for the April dates, then back to May again for M1 and so forth.

The data are beginning to look like a bell curve, but with many states allowing more freedom of movement, it is too early to tell if there will be a rise in a week or two.

The data are from


I use the download data file and create the chart in Excel.


Read more about statistics in these two books.


Creating Surveys on AMAZON










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

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Tuesday, May 19, 2020

Weekly Progress US Death Rates Decline May15




We have an evident decrease on weekly deaths for the 7-days ending May 15 2020. Downward progress (green columns) resumed after the May 8 increase (yellow column).

Legend

M21 to A25 and M1 represent the Month and Day. The numbers below the dates are for the 7-days including the date. For example, M1 = 11,989 deaths in the 7-days before and including May 1, 2020. The first M dates are for March, then A for the April dates, then back to May again for M1 and so forth.

The data are beginning to look like a bell curve, but with many states allowing more freedom of movement, it is too early to tell if there will be a rise in a week or two.

The data are from


I use the download data file and create the chart in Excel.


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

Follow this blog

My Page    www.suttong.com

My Books  
 AMAZON     GOOGLE PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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


Sunday, May 10, 2020

Covid Weekly Chart of US Deaths update





We have a slight increase on weekly deaths for the 7-days ending May 8 2020. Downward progress (green columns) has halted.


Legend
M21 to A25 and M1 represent the Monty and Day. The numbers below the dates are for the 7-days including the date. For example, M1 = 11,989 deaths in the 7-days before and including May 1, 2020. The first M dates are for March, then A for the April dates.

The data are beginning to look like a bell curve, but with many states allowing more freedom of movement, it is too early to tell if there will be a rise in a week or two.

The data are from


I use the download data file and create the chart in Excel.


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

Follow this blog

My Page    www.suttong.com

My Books  
 AMAZON     GOOGLE PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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


Monday, May 4, 2020

 Covid- 19 Weekly Chart of US deaths.




Legend
M21 to A25 and M1 represent the Monty and Day. The numbers below the dates are for the 7-days including the date. For example, M1 = 11,989 deaths in the 7-days before and including May 1, 2020. The first M dates are for March, then A for the April dates.

The data are beginning to look like a bell curve, but with many states allowing more freedom of movement, it is too early to tell if there will be a rise in a week or two.



The data are from


I use the download data file and create the chart in Excel.


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

Follow this blog

My Page    www.suttong.com

My Books  
 AMAZON     GOOGLE PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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





















Monday, April 27, 2020

Covid19 U S Deaths Weekly Chart



Are we there yet? The most recent weekly data suggest a downward move in the number of people who died in the past week.

In the previous chart, there appeared to be a channel or range between 1800 and 2000 per day with some anomalies. Now that we have more data, it is possible to group the data.

I am avoiding curves and means because it is not clear that there is a curve or that the data are normally distributed. The bar chart offers a clear picture of rapid increase and possibly (and hopefully a decline.

In this chart, I used weekly totals beginning with March 7, 2020 (M = March, A = April).

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

Date               Deaths

M21 213
M28 1447
A4 5450
A11 11620
A18 18277
A25 13963







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 PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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






















Tuesday, April 21, 2020

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 PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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






Measurement Error Standard Error of Measurement

In testing, measurement error usually refers to the fact that the same people can obtain different scores on the same test at different times. In a broad sense, measurement error can also refer to the degree of accuracy of a test to correctly identify a condition, which is discussed as test validity.

Recall that test score reliability is a necessary but insufficient condition for test score validity.

Many tests in psychology, medicine, and education are useful. The reliability of the scores will vary depending on such factors as the properties of the test itself as well as how well the user follows standard procedures in administering the test, environmental factors that can affect the scores, and factors within the person taking the test.

The scores on many tests conform to the pattern called the normal curve or bell curve. In classical test theory, the scores people obtain on tests are simply called obtained scores (symbol X). Statisticians consider the variation in scores to estimate a "true score." Variations of obtained scores around the theoretical true score (symbol T) indicate error because a reliable test ought to yield the same score every time it is used. The deviations of those obtained scores are referred to as error (symbol E). In a formula, X = T + E.

Theoretically, the reliability of test scores depends on the ratio of variances of the true scores divided by the variances of the obtained scores. A perfectly reliable test would yield a reliability value of rxx = 1.0. In reality, most of the better tests yield average reliability values above .90. Test publishers are obligated by professional ethics to include reliability values in their test manuals.

Studies of score patterns allow statisticians to calculate the average variability of score error. Thus, for any given published test, there ought to be a statistic known as the Standard Error of Measurement, which is abbreviated as SEM.

Once the history of the SEM for a test is known based upon large scale studies, users can use that value to estimate how the scores of test takers might vary if the test taker were to take the same test again under similar conditions. The estimates are based on the properties of the normal curve thus, the test must yield scores that conform to the normal score pattern to use a SEM based on this model.

Example, suppose a student obtains an IQ score of 100 and one SEM = 4 then on future administration of the same test, the student would likely score between 96 and 104 68% of the time.

The process of forming a range of values around the obtained score should remind users and test takers that scores are not fixed properties. Scores vary and they tend to vary in a "standard" pattern. In this theory, the error variance has been standardized. Clearly, a user who wanted to be careful could use 2 SEMs, which would then allow a range of plus and minus 8 points. In the example, the IQ could range between 108 and 92.

It is important to keep in mind that tests are neither reliable or unreliable because reliability is the property of scores not tests. Thus it is incorrect to refer to a test as reliable or unreliable. We can speak about the degree of reliability of the scores.

There are other theories about testing and reliability.

The concept of how well a test accurately identifies a criterion, see the discussion of validity.


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 PLAY STORE

FACEBOOK  
 Geoff W. Sutton

TWITTER  @Geoff.W.Sutton

LinkedIN Geoffrey Sutton  PhD

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






Declines in weekly US Deaths on latest chart

If the posted data are accurate, we have an evident decrease on weekly deaths for the 7-days ending May 22 2020, which is the far righ...