The two most interesting visualization are the wordclouds of three words phrases. Biden’s is first and then Trump’s.
Sentiment analysis showed only minor differences. However, the wordcloud’s show very different focus for both. Biden’s is characterised by more positive statements about issues and the need to defeat Trump. Trump’s on the other hand shows a strong focus on his slogans e.g. Corrupt Joe Biden.
Shows the proportional effect on Covid Deaths. Above the line shows greater than expected based on state population proportion, below shows less than expected.
The covid-19 death rate in the US is shown to have a statistically significant difference between between Afro-American (AA) and White populations. The graph below shows the AA proportion difference compared to the W proportion below the x=0 line. There is a clear difference across nearly all states.
The full outline, R program and data file are available at ameyenn/covid19
The PCA biplot confirms the difference. The vectors show a negative relationship between AA and W, AA is linked with the poverty vector as well. NY is the main outlier.
A basic cluster plot across all the data is shown below.
A t-test was performed with the following results, indicating a statistically significant difference.
Welch Two Sample t-test
data: dt[, 1] and dt[, 2] t = 3.7143, df = 80.722, p-value = 0.0003739 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: 0.3026568 1.0010984 sample estimates: mean of x mean of y 2.688740 2.036862
Australian sample is randomly chosen from 720 school forming a sample of 14,000 students. China sample is not random. It is skewed to the brightest students across 4 provinces nominated by the Chinese Government. This is the exception all other countries are sampled randomly.
The above shows the trend using the full Y-axis rather than exaggerating the decline by using a restricted access.
Climategate – as I understand it this is about the statistical techniques (trick) used to compare data sources and to ‘hide the decline’ of tree ring data from trees in Siberia after 1960 which were not consistent with other worldwide data. There have been plenty of enquires which all clear scientists of wrongdoing.
My conclusion is that there is not much that I can find to support the view expressed in a range of sites that the scientists were involved in a cover up.
Removal from Journal Editorial Boards or paper rejection
I am concerned about the claim that climate science can move into activist territory and be biased – there needs to be evidence, is there hard evidence that this is preventing contrary views being expressed?
On this brief review, I can’t find any evidence of a hoax, I find disputes, attempts to set record straight and to explain, possible confusion, accusations etc. all of which are classic in a complex change process.
The graphs below show the 1999 published data from NASA. On left there seems to be no pattern on the right the global temperature anomalies show an increasing trend. Anomalies are measured by taking the difference between yearly temperatures and the 30 year average, see the Y-axis, 1.0 means that the yearly average was 1degree hotter than the 30 year average. In the US the temperatures in the 1930s were very hot over a wide spread area, this is the dust bowl period.
The NASA 2017 graph shows the same data but has the data
from 2000 to 2018 shown and a statistical trend line.
Humansarefree.com make the claim that ‘this is significant scientific fraud’, there is no evidence for this and the trend shown should give rise to concern.
Heatwave Index
This graph is used to state that there is no discernable pattern
of temperature and that it was hotter in the 30s.
The Y-axis is not easy to interpret, but bear in mind this graph shows HEATWAVE conditions only, defined to be above the 10 year average over four consecutive days. The graph does not enable you to say if the average temperature is increasing or is the frequency of hot days increasing.
The graph is for temperature data across the US, the data shown on the following graphic is restricted to US cities.
This graph below shows the change in hot days and hot nights shown as a percentage of land areas.
How do we interpret the graph? Hot nights are on the increase, there is recent dip in day time temperature coverage of land. The trend line is upwards.
Finally, the clam 30,000 scientists are against climate
change dates to a petition circulating since 1998, there are numerous fact
checks on this and I feel at the minimum such criticism ought to be taken into
account before making such claims. Certainly they made Hoax claim.
In conclusion, the data and discussion on the Humansarefree
is misleading an does not attempt a sound analysis.
First observation is what data is being used to make this
claim and is it surface or lower atmosphere or sea surface data.
Spencer shows two graphs one for the surface and the other
for the lower atmosphere.
The graphs show temperature anomaly data, variation of
average temperature from 30 year mean. The trend lines on the data show an
increasing trend in temperature. Variations from year to year above the Yaxis 0
line indicate hotter.
I see no reason why one would conclude that there is evidence
for global warming slowing, in fact, it continues the trend.
Turning to the accuracy of climate models, again I can’t see
what the issue is here, the models indicate a similar trend. One would expect
variance from actual data, is it a statistically significant difference. (see http://iopscience.iop.org/article/10.1088/1748-9326/aaf342/meta)
for a nice balanced research article on the ‘pause’, which it refutes and
discusses the statistical issue.
Claim 2: Global
Warming is causing more and worse cyclones
The claim is misleading as it does not consider the broader view,
and implicitly is dismissing the role of more sophisticated models.
Claim 3: Global
warming is causing more drought, the IPPC claims there is no global trend.
The IPCC do claim on a global scale there is no evidence of
increased drought based on climate change, but not on a regional scale. This
aspect is discussed in the report and indicate areas like the Mediterranean and
Middle east are experiencing man induced drought.
“Rainfall averaged across Australia has slightly increased
since 1900, with a large increase in north-west Australia since 1970. A
declining trend in winter rainfall persists in south-west Australia. Autumn and
early winter rainfall has mostly been below average in the south-east since
1990.(climatechangeinaustralia, p1)
The claim is misleading and ignores regional differences.
Claim 5: Global
warming means less food
The evidence stated to refute this claim is the grain
harvest have set records in the past few years, there is no source given. There
are however many research papers and government sources which at the very least
ought to have been considered to give balance.
The claim is about the likely impacts of climate change, it is
a good point. However, that has been the case all along and I can’t see why one
would use the word ‘debunked’. It is a very complex area and such statements tend
to trivialize the matter.
Curry (https://judithcurry.com/2018/11/27/special-report-on-sea-level-rise/)
provides an independent research report on sea rise. It makes interesting reading,
but is not conclusive and has not been peer reviewed, it is published by her private
company. These latter facts should have been noted.
Claim 8:
Australia cutting emissions is not going to have any effect.
This is of course true, Australia accounts 1.3% of
emissions, with a proportion of 0.3% of the world’s population.
We also export a considerable amount of coal and iron ore to
two of the worlds leading emission countries i.e. India and China.
We will suffer the consequences of climate change over which
we have no control other than to (a) sensibly consider the matter and (b)
encourage others to take action. The best way to do this is by setting an
example. However, given our emissions intensive economy we have an enormous and
costly adjustment to go through.
Claim 8: Refutes Phelps’
claim that Kiribati and Tuvalu will disappear
due to climate change.
Kench’s research supports refuting this claim.
In conclusion, Andrew Bolt’s has presented many of the
claims before. What I have attempt to show here is that the claims are mostly
misleading and do not consider the broader picture. The article takes sides and
is not balanced, nor does it seek to take a balanced approach. There an
implication that consensus exists that climate change is real, but suggests
there less consensus about the significance of any change. The evidence provided
mentions two individuals, one a retired academic whose colleagues have ALL rejected
his claims, and one an independent company owner whose research has not been
peer reviewed, at least as far as I could determine. Such evidence is not
sufficient to support the main claim of the article.
Overall, the article is misleading and does not seek to add
materially to the publics understanding, rather it deals in contestable
generalities.
populations. The graph below shows the AA proportion difference compared to the W proportion below the x=0 line. There is a clear difference across nearly all states.
