Guest essay by John Davies *
Being able to evaluate the evidence behind any scientific claim is important. Being able to recognize bad science reporting or faults in scientific studies is equally important. These following points may help you separate the real science from the pseudo science.
Speculative Language
Speculations from any research are just that – speculations.
Look out for ambiguous, obfuscatary or weasel words & phrases such as …
– can, clearly, could, conjectured, considered, expected, may, might, perhaps, possibly, projected, robust, unprecedented
– “Experts suggest…” “It has been said that …” “Research has shown…” “Science indicates …”
“It can be argued…” “Scientists believe….” “A high level of certainty” “Models predict….” etc,
…as any real evidence, for the conclusions being claimed is doubtful.
Sensational Language & Headlines
The media will ‘Never let facts spoil a good story’
Words like – Unprecedented, unparalleled, unmatched, extraordinary, groundbreaking, phenomenal, apocalyptic, bizarre, cataclysmic, catastrophic, devastating, extreme.
Phrases like – ‘Since records began’, ‘The majority of scientists concur’ ‘Never on such a scale’: are used to convey a message, not necessarily the truth or facts, they rely on the reader having a short memory or being too lazy to check. ‘Unprecedented’; now often means…not within the last 9 months !!
Headlines of articles are regularly designed (with no regard to accuracy) to entice readers into reading the article.
At best they oversimplify the findings, at worst they sensationalise and misrepresent them.
E.g. – ‘Margarine makes mayhem in Maine !!’
Correlation & causation
Be wary of confusion by assuming that correlation equals causation.
See some entertaining examples – http://tinyurl.com/oqhw24g – 6 min.
Correlation between 2 variables doesn’t automatically mean one causes the other; there could be many other causes.
E.g. – Divorce rate in Maine has a 99% correlation with the consumption of margarine. http://tinyurl.com/qb4n9mf
(So is eating margarine, the cause or result of divorce ?…or are there other reasons ???)
Misinterpreted results
News articles often distort or misinterpret the findings for the sake of a good story, intentionally or otherwise.
If possible try to read the original research paper; rather than relying on ‘quotes’ from a news article (by a pressurised hack journalist on a deadline, who is trying to build a story to fit the catchy headline), roughly based on a poor press release.
‘Cherry-picked’ results
This involves selecting bits of data which support the conclusion, whilst ignoring those that do not.
Trend lines plucked from the middle of a graph may not show the real picture, you need to see the full graph to compare. If a paper draws conclusions from just a selection of its results, it may be cherry-picking.
Data Presentation
Check the start & finish points in every data set to pick up any cherry-picking. Look at the X Y scales on graphs, is one truncated to show a distorted result ? A neat often used trick is to just show the anomaly, so a small amount looks enormous.
Beware of graphs that suddenly go exponential, Are the results out of normal range ?? Look for the error bars, If there are no error bars, ask why ??
Graphs & statistics can help summarize data; but are also often used to lead people to make incorrect conclusions. This video shows a few of the many ways people can be misled with statistics and graphs.
-13 mins –
Journals and citations
Research published to major journals should have undergone a review process, but can still be flawed, so should be evaluated with this in mind. Similarly large numbers of citations do not necessarily indicate that research is good quality or highly regarded.
Un-replicable results
Results should always be replicated by independent research and tested over a wide range of conditions. Extraordinary claims require extraordinary evidence. You always need more than one independent study.
If it can’t be reproduced or the full data & methodology is not made available, then it’s probably another example of junk pseudo science.
Peer-review
The peer-review process** is supposed to be one of the cornerstones of quality, integrity and reproducibility in science & research. Peer Review does not mean the conclusion is correct.
It only means that it was reviewed by similar people for obvious errors.
Judging by the number of peer-reviewed papers that have had to be withdrawn in the last few years, the system clearly isn’t working any more: http://tinyurl.com/lahsgrl http://tinyurl.com/pwbsvzx
A scientist / journalist shares his story of 2 sting operations on the scientific publishing process with frightening results. http://www.sciencemag.org/content/342/6154/60.full & http://tinyurl.com/pweth63
“Of the 255 papers that underwent the entire editing process to acceptance or rejection, about 60% of the final decisions occurred with no sign of peer review. Of the 106 journals that discernibly performed any review, 70% ultimately accepted the paper. Most reviews focused exclusively on the paper’s layout, formatting, and language. Only 36 of the 304 submissions generated review comments recognizing any of the paper’s scientific problems and 16 of those papers were still accepted by the editors despite the damning reviews.”
It can be argued that the peer-review process has actually worked against reproducibility in research.
Desk top ‘peer-review’ has replaced reproducibility as the standard of good research.
Having your research pass a peer review is what gives researchers the moral license to say things like this.-
“Even if WMO [the World Meteorological Organisation] agrees, I will still not pass on the data. We have 25 or so years invested in the work. Why should I make the data available to you, when your aim is to try and find something wrong with it.” – Prof Phil Jones UEA 2005.
This cuts to the heart of the matter. Science must be falsifiable: otherwise it’s not science. Those who seek to find something wrong with your data are the first people who should have access to it, not the last.
Challenging, refining and improving other people’s work is the means by which science proceeds.
It’s not science until it has been reproduced several times over.
No matter HOW good the figures look, or HOW smart everyone thinks you are, or HOW pretty your graphs are – if you can’t reproduce the results on demand, it isn’t scientific – it’s just hinting in that direction. If a model is unable to predict direct observations, then the parameters, variables, or basic theoretical concept must be wrong. You should change the model ….NOT the observed data. The motto of the Royal Society of Great Britain is: nullius in verba – take nobody’s word for it. Never take any thing at face value.
Science is based on provable facts not blind belief;
Question everything.
But remember, the worlds most threatening words are – How, What, Who, Why.
John Davies is a retired engineer with interests in engineering, physics, history, power supply & transmission, steam engines & over the last few years the climate.
*Inspired by an original idea of Andy Brunning at Compound Interest http://www.compoundchem.com/wp-content/uploads/2014/04/Spotting-Bad-Science.png
** Peer-review alternatives http://tinyurl.com/pbdykgj & more importantly http://tinyurl.com/6souaom
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Predictive value.
It’s worse than we though. How are the kitchen renos BTW?
Nearly there. Thank you for asking!
“Bad Science” is really just a euphemism for “hive-science”, which is, in substance, a hustle, wrapped in a rip-off, inside a con-job.
And we know all this thanks to the boastful Professor Gruber whose flam-flam success with the general public derived, in his estimation, from the “stupidity of the American people”. Of course, us coolie-trash herdling-nobodies, whom Dr. Gruber holds in such contempt, are not really “stupid”, but rather we merely assumed that tenured academics, employed by our nation’s most prestigious institutions of higher learning, were individuals of probity, integrity, and good faith, instead of the trough-suckin’, brazen-hypocrite, carbon-piggie grifters we now know them to be.
But us much-abused peons do have the excuse that we’re, ourselves, men and women of wholesome good-character and honest-dealin’ and so we naively extended to our betters an assumption of the same admirable qualities. Our bad, but also a “lesson-learned” we can bring to bear in our future dealings with hive’s credentialed enablers and their oh-so-superior, smarty-pants airs.
Hey! you hive-tool, ivory-tower parasites!–we won’t be fooled a second time! We’ve wised up to your slicko, weaselly trickery, and we don’t believe, anymore, a damn word you sell-out, flunky, agit-prop hypsters have to say. See? we’re not so “stupid” after all.
mike, you forgot the ‘/sarc’ there . .
/sarc ; )
Seeing that my comment is in moderation and guessing as to why, might I respectfully ask the moderator to replace a likely offending phrase with “…repugnant subliminal resonances…” vice the original “…[snip], [snip], subliminal resonances…”.
@ur momisugly John
I see that my above comment doesn’t make much sense in isolation. But thanks for the “sarc” assist, John. I don’t use “sarc” tags, but rather try to make my crazy ol’ coot rants so over-the-top, extravagant, and outlandish that they’ll obviously register as a put-on. But I see I was not successful, in that regard, with my latest zinger, and so appreciate you helpin’ me out.
I mean, like, our betters would have us “good guy” lovers of Liberty and ethical science as just a scrofulous bunch of riff-raff “crazies”, so I give ’em “crazy”, and pile it on at the cyclic rate. Maybe with a little, subtle “dig” or “needle” thrown in, for good measure, on occassion. All good fun, of course.
I thought it was a fine post, mike . . keep up the good work.
PS~ That was the first time in my life I used a /sarc tag ; )
When the “science” does not include any observations made on the real planet earth, you should be suspicious.
G
And when the values reported, are not direct measurements of the variable reported, then it’s ok to laugh !
Uncertainties need to be listed at the outset.
Basic assumptions ( ie. data collection for example ) need to be examined for obvious flaws or poor collection methods.
Knowledge of all previous work in the field is also a must.
I would have thought a massive alarm bell would go off when data “have to be adjusted.” You have to have good knowledge of why a particular measurement or set of measurements is wrong, and by how much, to even think about adjusting raw data. Simply adjusting a data set because it looks wrong compared to others is not grounds. It is also pseudoscience.
I am sure William Briggs would have something to say about wee p values and other statistical contortions.
Lord Rutherford said: “If you have to use statistics, you should have done a better experiment.”
He obviously wasn’t talking about “climate science” or he would have left out the superfluous word ” better “.
G
If a paper lacks a hypothesis to test, it’s probably bad science. Papers should not begin with abstracts. The abstract should be eliminated, and the formal hypothesis inserted in it’s place.
That was before quantum physics … which for some reason reminds me of Schrödinger’s immigrant.
George E
That is one of the best quotes I have seen in weeks.
“He obviously wasn’t talking about “climate science” or he would have left out the superfluous word ”better“.”
Modelers talk freely about ‘experiments’ that are actually model runs.
When an engineer uses a formula for the deflection of a beam of some or other cross-section, they are running a model. When they conduct an experiment, they build a physical model of that beam and load it to measure the deflection v.s. load.
One can apply the formula 1000 times to produce 1000 modeled outputs for 1000 different shapes but none of them are experiments. They are mechanistic replications of a model. If the results have any validity or trustworthiness it is only because the model has been validated by experiments involving appropriately scaled measurements.
Considering the outputs of ‘climate models’ (GCMs) we observe that on balance the outputs are not confirmed by measurements. A close inspection of the measurements for precision and representativeness giving rise to arguably valid adjustments has not resulted in broad agreement between the modeled and the measured. All it has shown is that even at the extremes of plausible excuses, the modeled predictions of performance are, on average, quite incompatible with the measured values, with high confidence.
Obviously one could point to individual models that are in broad agreement with the measurements and say, “This one model seems to produce outputs in good agreement with the measurements.”. But that is not what happens, is it? Such models are apparently ‘working well’ but in order to get such good temperature agreement, they have to be tuned with a low sensitivity to CO2. That of course is anathema in the alarmist community which has as a point of departure a “dangerously high” transient climate response to a doubling of the CO2 concentration.
It is impossible to conclude anything other than the alarmists are not seeking understanding and insight, but rather influence and mere money. In academia the payoff is ‘having guessed right’ the first time they were asked. Fallibility is anathema in academia.
Edison would have made a terrible academic because with just one product alone, the light bulb, he was wrong about 1000 times and only right once. He would have been laughed out of any academic position as ‘having never been right once’ long before he succeeded. He was however a devoted experimentalist who shed a great deal of light on the difference between models and reality.
@Crispin Where I work, we have CAD analysis tools to check stress and strain on brackets to give us a good feel what will work and not crack or break in a vehicle over time but we also have to run tests on the real production tooled parts.
Ryan, thanks.
We call that validation of the model, right? That is how things work in the real world.
In science, the burden of proof lies with the positive assertion. For a claim to be accepted, the proposer must present sufficient real-world evidence for the null hypothesis to be rejected. AGW “deniers” are just asking for the real-world evidence. You don’t have to be an accredited scientist to play that role. You could even be a journalist! The predictions of a computer model, even if they turn out a hundred years hence to be perfectly accurate, are not today evidence rejecting the null hypothesis.
Bad science generally, not just climate science.
Honestly, the shoe is on the other foot. There is so much bad climate science out there that good science is the exception rather than the rule. The presumption should generally be that it is bad, and you need to be able to detect when it is good.
My favorite quote from “Galaxy Quest” goes here:
[bad guy General Saris]: “Let me tell you, sonny — I am a General. If you’re counting on me to blink, you are making a deadly mistake.”
[good guy Cmdr. Taggart]: “Well, let me tell you something, Saris — you don’t have to be a great actor to recognize a bad one. And you’re sweating!”
Add in anti-FOIA tactics on the back end when people start to ask why the data and models are not made available even though an end-of-world claim is being presented and cited by warped policy makers and biased journalists. There is also the basic question of why health science research and drug research is held to a higher standard while life-ending AGW climate change science is not.
Throw in wild cries about people trying to suppress science, when all they did is ask to see your data.
Resourceguy: Health science may be one thing, but don’t hold up pharmaceutical research as being something that has a standard worthy of emulating. It is totally corrupted by the huge amounts of money that the big pharmaceutical companies have at stake. This is one case that got aired in public – it’s probably the tip of the iceberg:
https://ethicalnag.org/2009/09/08/sheffield/
A good article on how to develop your own B.S. meter… Something that is quite necessary these days in order to protect your sanity from both the MSM and the journals. Thanks…
As with money, bad science drives out good science.
If the conjecture will not be known to be true, until the researcher’s retirement date, then ask that his(er) paycheck be dated the same as the retirement date.
G
Seconded
Yet one must allow us our errors.
I have been deep into USHCN data. Being a game designer, it was relatively easy for me to diagnose the fatal fallacy. It was an error. A starkly significant error, but merely an error nonetheless. The sort of error that I can easily make, myself.
It was compounded by a heavy side of confirmation bias [the Great Enemy], but human nature is. I would not want to dock a man’s pay for that sort of an error.
No one said pay was being docked, just delayed.
Gresham’s Law: “Bad money drives out good.” A more explicit version is: “Money overvalued by the state drives out money undervalued by the state.” Mutatis mutandis, “Science overvalued by the state drives out science undervalued by the state.” This doesn’t seem to be a true parallel, however. The reason bad money (silver coins adulterated with lead) drives out good money (pure silver coins) is that people can realize the greater value of the pure silver coins. Unfortunately, no one can realize the value of the good science that is driven out by the bad science.
That’s right Bloke. Bad scientists will publish more papers, perhaps get more grants because they force their findings to agree with what the funding organization. A useful indicator to me is to look at the number of authors. I there are 10-20 authors it stinks of politics, collusion to add names who didn’t contribute, etc.
What ever happened to split sampling data where half or so of the data are used to develop the model/relationship and then that model/relationship is tested with the other half of the data?
‘Science must be falsifiable: otherwise it’s not science.’
I think I understand what that means BUT I’m worried that many laymen think it means the opposite – hence they get confused. It’s very difficult to make a point to someone who is confused by the jargon!!!!!
Lol! I was wondering if someone would post this on here.
Our municipality is adding a stormwater charge of $15 per month, because in their view, it has risen higher than ever. Yet when I checked Environment Canada’s precipitation data, there is no trend here, it’s fluctuating on a linear trend.
Sounds like it’s time for ‘letters to the editor’, copying the members of the town council.
You left out “We were surprised to find” as a red flag in conclusions. That sometimes means that they didn’t do a literature search up front where the result was well known for years in other fields or, no matter how hard they tried, they couldn’t find any data to support their foregone conclusions, but they decided to publish anyway and figure out later what was wrong with the data. (“More study needed.”)
We’ve seen a few of these ‘surprising findings’ here on WUWT over the years.
I’ve noticed projected temperature graphs are often slanted the same as projected CO2 graphs.
projected surface temperatures
CO2 graphs
Even though they have radiative transfer as logarithmic, they believe in positive accelerations too. Which somehow, in their minds, even things out – makes the whole relationship linear. I don’t know, seems like collectively they might not be as smart as they think they are.
Those were the good old days! Not the “Bad Science” (BS) part, but the science fiction. You wouldn’t believe how many of those I read. 🙂
Another good clue to spotting bad science reporting is if its in ‘The Guardian’ environment pages.
The motto of the Royal Society of Great Britain is: nullius in verba – take nobody’s word for it.
What a joke! The “ruling elite” of the Royal Society is totally entrenched in the Warmist camp.
Professor Michael Kelly, writes ..
“Five years ago, I was one of 43 Fellows of the Royal Society who wrote to our then-president about its approach to climate change. We warned that the Society was in danger of violating its founding principle, summed up in its famous motto ‘Nullius in verba’ . The reason for our warning was a Society document which stated breezily: ‘If you don’t believe in climate change you are using one of the following [eight] misleading arguments.’
The implication was clear: the Society seemed to be saying there was no longer room for meaningful debate about the claim that the world is warming dangerously because of human activity, because the science behind this was ‘settled’.
We hoped we would persuade the Society to rethink this position. That document was revised so that the uncertainty involved in trying to model the climate was admitted. But since then the Society has become more, not less dogmatic – despite the fact that since we sent that letter, it has become evident that there is even more uncertainty than previously thought. Carbon dioxide levels in the atmosphere have continued to rise, but since 1998 there has been no statistically significant rise in global temperatures at all”.
You mean, this Royal Society?!! Which respects the appalling anti-scientific agenda of Lewandowsky?
The man who claimed to show an association between climate change skepticism and conspiracy ideation.
Except that his self-style “study” was pure junk. Calling Lewandowsky’s work voodoo science would amount to a complement. Voodoo science is science that is intended to “look like science”. Lewandowsky’s efforts fail to fulfill that requirement. Pseudoscience or junk science, perhaps. Not really science at all, though.
“The Royal Society, London, 6-9 Carlton House Terrace, London, SW1Y 5AG
Following the 2015 Paris Climate Summit, countries from around the world have backed climate science and committed to reducing emissions. But for years, public and political uncertainty has delayed cooperation and action. Why has uncertainty had such a powerful psychological effect on us and why is it so damaging?
Cognitive scientist Professor Stephan Lewandowsky is a Royal Society Research Fellow in the Department for Experimental Psychology, University of Bristol.”
from: https://royalsociety.org/events/2016/02/uncertainty-us/
As a correction to my above comment (awaiting moderation), where I said voodoo science – I was thinking of cargo-cult science. That’s a better description.
I beg to differ indefatigablefrog
The cargo cult is based on something real. Airplanes really did drop from out of the sky bringing tools and goodies. At least occasionally. The cargo-cultists build, as best they can, from memory and the materials at hand, ‘decoy ducks’ in order to attract the flying machines to return. They do everything within their power and understanding of the universe to attract the benefits contained in those flying machines.
Climate cultists are not in the same league. They are not true believers. Hardly a one of them. They are mendacious cherry-pickers trying to sell a catastrophe they invented from whole cloth. The noble-cause-corrupt would be the true believers. It is easy to convince oneself with personal research that these guys know they are wrong but are covering up the evidence, manipulating the data misrepresenting the whole truth and mounting personal attacks against those who are effective in pointing out their errors.
Voo-doo science is what they do: creating caricature dolls of their enemies and sticking in the pins of calumny, gossip and false accusation hoping that some harm will magically befall them. The rejoicing over the death of one of their exposers, revealed in the Climategate emails, who they needled needled years, is a classic example of voo-doo science practitioners in full voice.
Let’s not demean the well-intentioned cargo-cultists of the Pacific Islands by lumping them together with this lot who can’t even plot their data sets the right way up.
Legacy Pal Review is so 20th century .
Articles get thoroughly peer viewed , reviewed and responded to within hours when posted here .
Seeking Alpha is another seriously instantly peer reviewed site .
Independent review. (A modest bit of it, anyway.)
That’s where the game is played.
Peer review is just a door pass to the arena. But sooner or later you gotta do in the tiger. And if you fiddled peer review, long odds are that the smile will be on the face of the tiger. Why else are so many papers falling headlong and flat on their paces within a month of publication? Fiddled or lax peer review let them down.
“bad science”? In my laymen’s opinion, climate science is a ‘soft’ science. It cannot be bad as it was not good to begin with. Conversely, the minute climate scientist crossed into the social fray and political debate it stopped being science altogether. If I can make those distinctions.
Well it would seem that just believing that such a thing as a global climate exists, is a reason to change the channel.
A ten mile road trip can be enough to wipe out 160 years of climate change.
That’s just my opinion of course. Based on the presumption (AKA WAG) that ANY local region/place/station/whatever should be expected to have a map of its own local ” climate anomaly ” that looks not at all unlike the five or more very famous and ballyhooed periodically (monthly) reported global climate anomalies.
So YOUR local climate anomaly history, should look just like GISS/RSS/UAH/HADCRUD/NCDC/whatever. That is if you have ever bothered to track it.
So if you can’t change your mean Temperature history by say 1 deg. F or 0.6 deg. C with just a ten mile move to someplace else, then you probably are living in Victoria Kansas, or some other equally boring place.
G
PS VK is the place where I had a valuable 1956 Jaguar XK140 hardtop coupe totaled by an empty logging truck. it is 500 miles from VK to the nearest loggable tree !
George E
Man, that I ba-a-a-ad kharma.
Adjusting results to match the theory, rather adjusting the theory to match the results.
Anything authored or co-authored by John Cook, Lewandowsky and Company, or any group in which the lead author might be an “actual Earth scientist” of some kind, but the rest of the authors are either friends, blog commenters, naive undergrads, or winners of some sort of contest…like “Guess the number of Co2 molecules in the Jar” or “Design Dana’s Newest Book Cover…PLEASE!” Such papers are easily identified by the overwhelming slick “widgets”, “sticky phrases” and marketing sound-bite-phrase to data points ratio. Be on the lookout for old words used in completely unique and unusual ways…such as “leakage”, “consensus”, and “expert”.
“Something like 55% of the modeling done in all of science is done in climate change science, even though it is a tiny fraction of the whole of science. Moreover, within climate change science almost all the research (97%) refers to modeling in some way.”
See:http://www.cato.org/blog/climate-modeling-dominates-climate-science
I would also add that modeling is not science. Modeling output is not “observation”. Models are primarily used for projection or prediction. But before models can be useful for any form of projection or prediction, they need to be verified and validated, to ensure that they accurately represent the significant elements of the real world that they are modeling. To the best of my knowledge, no climate models have ever been verified and validated.
Which is why Bob Tisdale found that climate models, irrespective of whether they resulted in a positive or negative Top of Atmosphere energy imbalance, always seemed to produce global surface warming. See figures 5, 6 and 7 here:
https://wattsupwiththat.com/2016/03/01/climate-models-are-not-simulating-earths-climate-part-4/
Climate models are bad science.
I usually don’t get to the bad science, as I stop reading when I get to “model”, unless its related to Kate Upton.
Its generally: published paper (with an increasing number of them being retracted), headline, lede, qualifiers (always near the bottom of the story), and they don’t want you to notice that none of them say the same thing.
I wish someone could turn this into a dictionary:
http://www.numberwatch.co.uk/FAQs.htm
Always look for data dredging, and the Trojan Number
http://www.numberwatch.co.uk/data_dredge.htm
http://www.numberwatch.co.uk/trojan_number.htm
Most people will actually almost brag about innumeracy, which someone who is illiterate is shamed. Which makes this almost tragic:
https://www.thestar.com/yourtoronto/education/2016/05/13/for-many-teachers-math-just-doesnt-add-up.html
Er, please read “while someone” for “which someone”. Literacy and all that…
Never bother with an article in the press that does not link to the underlying formal paper: read the paper rather than the article.
The error I find most often is that the conclusions conclude more than the analysis justify.
Some added kudos to Darrell Huff “How to Lie with Statistics”(1954)
With regard to the distortion of presentation of information – I would like to volunteer all graphs showing a switch from tide gauges to adjusted satellite rates of sea level rise as the most egregious currently circulating example.
Especially ones that truncate the tide gauge data at 1993 – rather than showing it alongside the satellite based product.
Even worse when the purported acceleration is extended later into the century.
This kind of monstrous abuse of trust in science should really be laughable.
We should be able to laugh it off and point out the obvious error upon which this is based.
But, currently only the alarmists are laughing about this.
They are laughing all the way to the bank.
Or perhaps they really believe it – in which case we are dealing with people who are suffering from a terrible long term hallucination. And they are at large and wielding influence. Climate alarmism really is scary.
Inasmuch as it is scary that complete imbeciles have obtained so much power.
http://www.realclimate.org/wp-content/uploads/NYT-sealevel.jpg
It’s actually much simpler – real science requires falsifiability. Simply put, a necessary and sufficient falsifiable hypothesis statement:
1) a list of observations, which if observed, mean your hypothesis is false;
2) a logical argument that the lack of those falsifications means that your hypothesis must be favored over all others (including the null).
If you cannot provide #1 and #2, you’re simply picking at the edges of speculation – which, may be a good thing to generate ideas, but are not proper science until put through the filter of falsifiability.
I never touch margarine and I’ve been married for thirty years … but, I live in Florida.
What does this mean?
I have no idea Lorcanbonda but what you and your partner do at the beach with melted butter is your business……I am trying not to think about it……. 🙂
Who is this margarine person, and why does your spouse want you to touch her?
Whenever I see a time series graph I always look at the start and end year dates and ask why does it start where it does and more importantly why does it stop before the current year.