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Data say the Darndest Things

Apparently I’m late on the bandwagon for spotting this one, but twitter is atwitter with news that it’s cold in Washington D.C. right now. A propose of my last post, Chairman the Senate Environment and Social Works Committee and Amateur scientist, James Inhofe (R-OK), brought a snowball into the B-zSXewUIAATlKMSenate yesterday as data against the notion that Climate Change is occurring.  “We hear the perpetual headline that 2014 has been the warmest year on record,” he said.

Apparently he meant to say that climate can change, but that humans have no ability to effect this kind of change directly. As he states on his webpage:

“The climate is changing, as it always has been changing, and always will, there’s archeological evidence of that, there’s biblical evidence of that, there’s historic evidence of that, it will always change,”Inhofe said.

But more interesting to me is his data gathering.

datapoint 1: Snowball in Washington D.C. February 27

datapoint 2: “It’s very, very cold out.”

conclusion: It is unseasonably warm.

Senator Inhofe should spend some time with Darrell Huff. Huff’s classic text, How to Lie with Statistics is one of my favorite books. It’s a bit out of date with its examples, but still a fun, easy read. And more importantly, a good look at how data can be manipulated to appear to represent a picture different from reality.

CongressIt all comes down to data collection and interpretation. As Senator Inhofe did, I could easily gather some quick data from my immediate surroundings, ‘ 100% of the people I had breakfast with live in my house’ and derive a quick conclusion: ‘everyone in the world lives in my house.’

Or, I could go more subtly and use data closer to Sen Inhofe. Right down the hall in the other house of congress sit enough data to clearly demonstrate that employment numbers are climbing steadily with no sign of this so called ‘great recession.’ In fact, no sitting member of Congress has ever been unemployed while serving in congress.

Actually, the important point to make is that science can be done well, but it can also be done poorly. When it’s done poorly, it can be due to a number of reasons, such as poorly designed experiments, lack of appropriate controls, inaccurate data collection or poor choice of samples. All of these can happen without any intent to deceive, however, any experiment done with a conclusion already in hand is inherently partisan and is bound to produce unrepresentative results. Science should not be politicized, doing so generates flawed data and erodes public confidence in both our lawmakers and our scientists.

I have no problem with science being presented in congress, but I do think that it needs to be done responsibly and in careful consultation with those who understand the entire scientific process.

Does your congress member have a scientific advisor?

I’ve just written to my Senators and Representative to ask that question directly and I hope to hear back from them soon. I’ll be sure to post their answer here.

 
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Posted by on February 27, 2015 in Uncategorized

 

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Undisclosed Funding – or – How to Look Like You have Something to Hide

Apparently disclosure of funding sources does not seem to be a important to some researchers. In Paul Offit’s Autism’s False Prophets, Andrew Wakefield’s failure to disclose $800,000 given to him by Richard Barr’s law firm to link MMR vaccine to Autism is a major factor contributing to his decline and fall. In Wakefield’s case, he failed to disclose any conflicts of interest as required by the journal, The Lancet, where he published his work.

The Lancet’s Author Instructions state clearly what may constitute a conflict of interest and that anything giving the impression of a conflict should be reported to the editor.

A conflict of interest exists when professional judgement concerning a primary interest (such as patients’ welfare or validity of research) may be influenced by a secondary interest (such a financial gain). Financial relationships are easily identifiable … A conflict can be actual or potential, and full disclosure to the Editor is the safest course.

At the end of the text, under a subheading “Declaration of interests”, all authors must disclose any financial and personal relationships with other people or organisations that could inappropriately influence (bias) their work.

Wakefield’s failure to report the potential conflict of interest both to the journal and also to his collaborators. Unsurprisingly, both groups were upset when they learned about the money. Eventually, along with alleged ethical violations, Wakefield had his license to practice medicine revoked and his paper retracted.

524990main_FAQ10_fullOne would think that this would serve as a warning to those with similar perceived conflicts, suggesting the best course of action to be one of full disclosure. In the end, it is often easier to defend a potential conflict that the author puts forward him or herself, rather than having to retroactively explain why information was withheld and then try to demonstrate that any conflicts did not impact the quality or findings discovered.

Nevertheless, The New York Times has published an account of a very similar situation in climate science today. In their article, Deeper Ties to Corporate Cash for Doubtful Climate Researcher, the case of Wei-Hock Soon, a scientist at the Harvard-Smithsonian Center for Astrophysics who claims that variations in the sun’s energy can largely explain recent global warming is being investigated for the influence of cash on his findings.

The crux of the times article is that Soon…

… accepted more than $1.2 million in money from the fossil-fuel industry over the last decade while failing to disclose that conflict of interest in most of his scientific papers. At least 11 papers he has published since 2008 omitted such a disclosure, and in at least eight of those cases, he appears to have violated ethical guidelines of the journals that published his work.

The disclosure of Soon’s funding does not mean that his data were influenced by the money, however, keeping it hidden definitely leads to questions. Not the least of his problems comes from using terminology such as ‘deliverables’ to describe his papers and preparations for congressional testimony in communication with his supporters. The term ‘deliverable’ is defined by business dictionary.com as a “Report or item that must be completed and delivered under the terms of an agreement or contract.”

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Although these articles are not within the timeframe of the financial contributions alleged in the Times, these help to clarify Soon’s position on climate science. These publications include:

“Recent Warming is not Historically Unique”.  Callie Baliunas & Willie Soon (2001.04.17)Capitalism Magazine. In which he concludes “The facts are simple. The Little Optimum and Little Ice Age were real. They were also widespread over the globe. The twentieth century is not the least bit climatically unusual. So why the recent media hysteria that the twentieth century is the warmest of the last 1,000 years?”

“Variable solar irradiance as a plausible agent for multidecadal variations in the Arctic-wide surface air temperature record of the past 130 years” Volume 32, Issue 16. August 2005. Geophysical Research Letters. As the title suggests, this article attributes recent climate data to “features that are highly correlated with the Sun’s intrinsic magnetic variability especially on multidecadal time scales.”

 
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Posted by on February 25, 2015 in Uncategorized

 

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Immunology – Aquaman style

I almost split a seem the first time I saw this cartoon several years ago.

 
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Posted by on February 11, 2015 in Uncategorized

 

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Blood and Genetics

Blood type is a fun and easy way to get to know genetics and learn some practical applications. In the simplest of ways, the three basic blood types are A, B and O.

A good place to brush up on blood type genetics is wikipedia, which has an excellent article on the topic.

Once you’ve reviewed this material (if you need to), then go to nobelprize.org to play a game about blood transfusions (all based on simple blood type genetics).

While you’re on the site, read a little about Alfred Nobel and why it was so important to him to have a lasting positive legacy.

 
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Posted by on November 3, 2014 in Uncategorized

 

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Variables

imagesThe Fall Semester is starting soon and I have to say: ‘what a relief’. Going all summer without teaching is difficult, yet I always avoid summer classes because I’m worried that I will get myself into trouble with vacation plans or childcare responsibilities. But all that ends soon and I can get back in the classroom, start thinking (and writing) about science, and stop writing so much about movies and TV.

I’ve nearly finished one of my two iBook- format handbooks that I need to have ready for when classes begin. This year’s book is much more interactive, with review questions at the end of each chapter, keynote presentations of my lectures and some video animations. In writing it, I got a bit hung up on my day 1 material. Namely, the scientific method. This is the method developed by Descartes and others to help us figure out the difference from what is true about the world and what isn’t – although saying it that way makes it sound more clear and 100% accurate than it actually is. In reality, the scientific method is a way of thinking that is based on ‘verity and validity.’ What it is best at is determining what is NOT true. However, over time, that steps us ever so slightly closer to an accurate understanding of the way the universe works.

On the one hand, the scientific method is a very precious thing. It comes from the realization that our senses and our minds often fool us. We evolved in a world rife with danger and it made a lot of sense for us to see connections in the world – even when they were not really there. Because, as many evolutionary biologists will explain, the person who assumes there is a lion behind every bush tends to live longer than someone who does not – especially when there are occasionally lions lurking behind the bushes.

Once we escaped that world, created civilization and put an end to the lion problem, we started to wonder, “How does the world work?”

VariableTo answer that question, we could make up ideas and just cling to them so long as they appear to be at least make a consistent story (I’m thinking Aristotle), or, we could test our ideas and see what we get.Which brings us back to the scientific method.

For the most part, however, most scientists don’t really frame their ideas in the form of this method, but have internalized the method and just apply the principles. What I mean by this is, every introductory science book talks about independent and dependent variables, etc. but I have never actually heard anyone describe their experiments in these terms. Instead, we talk about conditions, controls, data and conclusions. Despite working in science my whole adult life, I still have to look up the difference between independent and dependent variables – and I don’t use these terms in my class unless someone asks about them. Instead, I spend much more time focused on setting up an experiment and thinking about what controls would be needed and how someone may interpret the data. I also spend a lot of time early on asking what data really tells us. What’s the difference between correlation and causation, are we reading too much into our data? Can there be other explanations for the same results?

But, having though about this a bit today, I wanted to ask (although I see that my readership has really died off over the summer) what people thought about these terms?

Do any of you actually think these terms are important to teach students? Do you regularly use them in your work? 

 
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Posted by on August 3, 2014 in Education

 

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It crawls… It creeps… It eats you alive!

Compounded Interest

How money or value or perhaps even The Blob grows. In the simplest of all settings, interest can be as straight forward as, I’ll loan you $10 for a hamburger today, and you pay me back $11 on Tuesday. In this case, Wimpy is taking out a loan of $10 at 10% simple interest.

That’s great for a cartoon, but it’s not the case in most real-life examples of interest. In real life, a loan you take today might accrue interest every year, month, day, or even continuously. Although the last case is one of the most interesting ones as it deals with a special number ‘e’, I just want to address the more intuitive cases.

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Clean Shaven Man

Let’s say Wimpy is keen on that hamburger today, but he won’t have any cash until Tuesday again. This time, his usual rubes are all cash strapped as well, so poor Wimpy has to go to a formal lender. This lender is OK with the loan, but as insurance against Wimpy’s ability to pay back the loan on time, he insists on compounding interest every week.

“Let’s be clear about this Wimpy,” his loan officer says, as he walks him through the conditions. “You can have your $10 today at 10% interest. The loan is due on Tuesday, and that will come to a total of $11. If you can pay it off then, great. But if you need more time, we will be compounding the interest – that means that you will essentially be getting a new loan of $11, at the same 10% rate.”

“OK,” says wimpy and leaves his mark on the loan document.

 

This is exactly the right way to think about it.

  1. initial loan is made: $10 at 10%, due in one week.
  2. If the loan continues, another 10% is charged on the new total.
  3. Week after week, this goes on until Wimpy can pay up or he’s referred to collections and they repossess his barbershop.

 

Mathematically, this takes the Principal (loan amount ) and multiplies it by 10% every week.

  1. week 0: $10
  2. week 1:$10 + 10% = Principal x 1.1                                                          -> $11.00
  3. week 2: ($10 + 10%) x 110% = (Principal x 1.1)2                                              -> $12.10
  4. week 3: (($10 + 10%) x 110%) x 110% = (Principal x 1.1)3       -> $13.31

 

This can be generalized by the formula:

Amount owed at time      t = P (1 + R)t

Where P = principal

R = rate (expressed as a decimal)

T = the number of times interest is compounded

(whether its days, years, months, whatever)

(10)(1+.1)3               -> $13.31

 

This goes for any compounded growth.

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oooo – Air Conditioning!

The Blob arrived in Downingtown, PA in 1958. At first it was just something riding into town on a meteorite. But soon after, an old man touched it and got it stuck to himself. Steve McQueen comes to the rescue and gets the old fellow into town to see a doctor. Meanwhile, it becomes evident that the blob is not letting go, and is hurting terribly. Dr. Hallen decides to amputate, but before he can, the blob grows large enough to eat the old man, then a nurse, and then the doctor.

From then on, the thing just keeps growing. Let’s say it grows at a rate of about 50% an hour and use the same formula…

 

  1. hour 0: 100g
  2. hour 1:100g + 50% = Principal x 1.5                                             -> 150g
  3. hour 2: (100 + 50%) x 150% = (Principal x 1.5)2                                               -> 225g
  4. hour 3: ((100 + 50%) x 150%) x 150% = (Principal x 1.5)3        -> 338g
  5. hour 24:         ——-à                                                                       ->1,683,411g

 

You can really see how this thing gets huge fast (or at least massive, we never talked about the density of this thing).

Graphically, the blob’s growth looks like this:

Image

One troubling thing is that this could also represent the balance on a credit card that isn’t attended to.

“It crawls… It creeps… It eats you alive!”

-Tagline, The Blob 1958

 

For a good explanation of interest, compound interest, and ‘e’ – check out Khan Academy’s lectures on this or this site that does a great job illustrating the difference between several types of interest.

 

 
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Posted by on June 13, 2014 in Uncategorized

 

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We’ve known for years that we can raise our IQ by eating gifted children

Or, we could if experiments done in flatworms translated directly to humans. If you haven’t read about James McConnell’s experiments with Planarians and memory transfer, I urge you to do so, if only just for the opportunity to read science writing that sounds as if it was ripped directly from the pages of Mary Shelley’s Frankenstein. It also turns out that their blood is carrying some youthful factor that we want as well. The trouble is getting it out of them and into us. One might immediately think of vampires – which is not a bad place to start, but it might require a bit of refinement.

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Get ’em while they’re smart!

Science magazine from 9 May 2014 informs us that there is something soluble in the blood of young mice that, when transferred to older mice – well, to put it simply, it rejuvenates them.  “The therapeutic implications are profound if this mechanism holds true in people,” says Matt Kaeberlein in the News and Analysis summary accompanying the article.

This article captured my interest and made me want to write about it for several reasons. First, this is effectively a ‘Fountain of Youth’ experiment – and it seems to work! Researchers have long wondered: what keeps the young, young and makes the old, old? What changes as we age? Can we stop it? Reverse it?

In terms of ethics, should we even be looking at age as a disease? Or is it just something that happens and needs to be accepted?

ImageMost notably, work has been done to show that telomere length and the enzymes that maintain it, may be intimately involved in the aging process. Telomeres are sections of non-coding DNA at the very ends of chromosomes that consist of a number of sequence repeats. The thinking is that these DNA elements are maintained (by telomerase) in order to prevent the chromosomes from getting attacked and destroyed by nuclease enzymes. I think the Ponds Institute has been working on this for years 🙂

The other interesting thing about this work is the technique that gave us the data in support of this hypothesis. It’s a fantastic experiment called parabiosis. From the Greek you can see that this ‘living with one another’ experiment involves making artificial siamese twins of two mice, an old one and a young one.

I hope to be able to discuss this procedure in some detail in upcoming posts. But, until then, let us be satisfied that the technique was done. This now permits the intermingling of soluble blood products between one (clonal) mouse and another. When it’s done, something, crosses from one animal to the other. This provides cellular cues to the fact that something from this young mouse has been lost in older mice, but if it could be restored, it would result in (at least some) regeneration of youth.

– I’ll come back and revisit this more in the future to explain what has actually been observed and also to discuss some other interesting experiments carried out using this parabiosis technique. Right now I’m falling asleep and violating a new family rule on computer time to boot!

 
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Posted by on May 25, 2014 in Uncategorized

 

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Freakonomics Questions Podcast: Too close to home?

ImageHow to Think Like a Freak.

That’s the title of the new Freakonomics book just out this Monday, May 12, and it is also the name of this week’s Podcast. It’s a good show and a good premise. However, as a scientist (well, biologist – but it counts!), I think that calling this a show /book about economics is incorrect. It’s really a show about science. Or at least the application of scientific method to problems that are often not tackled by traditional scientists, but by their more handsomely paid colleagues, economists. Or by their equally unhandsomely paid colleagues, sociologists and psychologists.

It shouldn’t be something I stop to point out, but it is somehow troubling to me to parse science. It probably means more about me than it does about the actual topic to say this though.

Nevertheless, the current episode is a combination Q&A and book promotion. Which is why I need to point out that sometimes it is hardest for us to look critically at the things that are near to us. This is exactly why we are judged by a jury of our peers – people who may be able to relate to us in some way, but who are also not emotionally involved in the crime.

Several things struck me in this episode that I considered writing about. One was the questioner who asked about the current fetishism of bacon. It turned out that the question was examined just as I thought it should be: one part seriously considering the question and one part reading the assumptions and position of the questioner.

I put that one out of my mind. Then there were two questions that brought up the financial motivations of Levitt and Dubner. The first was about whether it might be worthwhile to have a tiered questioning scheme in which listeners could pay money to give their questions higher priority, i.e. the highest tiered questions were guaranteed to be answered on air, while lower tier questions would only be answered if they met other quality standards.

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Levitt

Levitt and Dubner addressed this question well too, saying that it would undermine the quality of the show to do this, while also raising an interesting question about the pricing of these tiers. Would they be priced only to separate the listeners? Or would this actually be meeting some financial goal of the show’s producers.

In the course of the discussion, Levitt said this:

LEVITT: And our podcast is defined by a relationship in which we give it away, and we don’t really do this for money. I’m not sure why we do it, but I don’t think it’s for money. It can’t be for money. And so, to then change the frame that this is about money.

then, backing this up further, when the question about how they could participate in a fundraiser for NPR if this show was not, in some way, about the money:

But that makes me feel bad, we shouldn’t have taken their money. Why would we take their money, we’re just doing this for fun. It feels horrible to take their money.

A second question comes in also questioning the financial motivations of the show’s hosts:

 from Meredith Summers. “Hello, I wonder if it would be at all possible to quantify in financial terms Steven Levitt’s contribution to the University of Chicago? For example, does his fame bring in more students who hope to work with him and learn from him, and is this contribution commensurate with his salary.

This question was considered in a number of interesting ways. First, Levitt made clear that he was paid very well by the University of Chicago, and had nothing to complain about there. (I’m glad to hear this. It always makes me happy to hear about academics doing well. It’s so often the case that academics are disenfranchised from their knowledgable contributions, that it is comforting to know that this does not happen at the best Universities.)

They also spoke about the difference between the way Universities take ownership of inventions (they do) vs literary contributions (they don’t). I expect that this is probably due to the bargaining power of academics at the time that each of these legal questions came up for discussion and the argument that being a professor may not actually drastically help you to write a book, whereas many inventions require the infrastructure that a University supplies). “It reminds you of alcohol versus marijuana in that if you were starting over from scratch there’s no way these two would be so different,” Dubner comments.

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Dubner

But still, the question remained largely unanswered. “Why do the show?”

I think there are several reasons why they do the show. The first, they cover: because it’s fun, and it’s cool to do things that are creative and fun. I would feel the same way.

But the part of the answer that is a little too close to them to either see, or to admit, is that the podcast / radioshow promotes their books. It’s right there in the ‘About’ section of their website. Blah, blah blah, wrote an article. blah, blah, blah, wrote a book. blah, blah. Book sold well. Podcast, blog, etc. etc. were born. Fun, yes. But it all fits together neatly as something they enjoy doing that brings more people in to buy their books so they can spend more time doing what they enjoy doing.

Like the quote that works so well for some people but not others, “do what you love and the money will follow.”

I may be getting a little dark here, but I’m not sure that always works…

Nevertheless, listen to the podcast, buy their books, you’ll love them. They’re filled with good questions and how they can be answered in a scientifically rigorous way. More power to you guys!

 
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Posted by on May 14, 2014 in Uncategorized

 

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A Sci Fi Reading List

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1/3

Check out this Reading Checklist:

http://www.buzzfeed.com/isaacfitzgerald/do-androids-dream-of-electric-quizzes

I scored a measly 30 of 99. I felt good with the top of the list, but further along, things fell apart.

 

 
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Posted by on May 11, 2014 in Uncategorized

 

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Bane of the Garden Gnomes

Last week, we discussed the use of the Hardy Weinberg equations to estimate the rate of change in population under conditions of extreme selection, i.e. total elimination of one phenotype. This is essentially the goal of any sort of eugenics program. As an example of a way that this kind of policy could creep into culture, we watched GATTACA. Besides, it’s just a good film.

The purpose of the Hardy Weinberg equations is to model conditions under which allele frequencies can NOT change from one generation to the next. Therefore, it is evident that these are exactly those conditions that are responsible for allele frequency changes.

These conditions are:

  1. No Mutation
  2. No Selection (survival)
  3. No Sexual Selection
  4. No Genetic Drift –due to occasional fluctuations occurring by chance
  5. No Gene Flow – immigration / emigration

In order to prevent the random changes in allele populations stipulated in #4, we also need a sufficiently large population, where sufficient is likely definable by someone with better probability-computing skills than my own. (I feel like going off half-cocked on notions of probability and finite vs infinite time, but I’ll spare you).

Anyway, if we know something about the population, we might be able to work out the allele frequencies and then compute our theoretical proportions for the next generation from the equations…

p+q = 1,

where p and q are the frequencies of the (only) two alleles we are calculating.

and

p2+2pq+q2 = 1

where each unit above represents the proportion of that genotype.

Mathematically, these equations provide insight into how rapidly the rate of an allele in a population could be eliminated if reproduction was prevented in a specific group. (This sounds completely esoteric without using an example, so let’s come up with one…)

A Healthy Gnome Couple

A Healthy Gnome Couple

Imagine a population of fictional creatures – Garden Gnomes.

These gnomes have a recessive allele that makes them susceptible to a fungal disease. We’ll call the two alleles for this trait H – hearty (resistant) and h– weak (susceptible)

There was recently a new law passed amongst the gnomes forbidding susceptible gnomes from breeding (let’s imagine that the H allele is apparent by a normal complexion and the h allele is apparent by a jaundiced complexion. Like susceptibility to disease, jaundice only appears in the homozygous recessive (hh) gnomes.)

Imagine a population starting with equal allele frequencies, p=q=0.5.

p2+2pq+q2 = 1

will give us genotype frequencies of:

25% HH   + 50% Hh + 25%hh = 1

for the present generation.

Now, if we start our draconian, anti-jaundiced gnome policy and prevent breeding of these individuals, then this generation‘s breeding population only consists of the HH and Hh gnomes, where only the heterozygotes will contribute the h allele to the next generation.

If we call the next generation q1, we can estimate the new proportion of the q allele in the population as the frequency of the heterozygote over the total population excluding the hh gnomes:

No wonder they want to get rid of these guys

No wonder they want to get rid of these guys

After one generation, the frequency of the H allele is now 67%.

Since the same process would occur generation after generation (as long as the law was in place – and followed), we can determine the frequency of q at any generation, where n is the generation number.

  1. From this information, try calculating the frequency of both alleles after the policy has been in place for 5 generations.
  2. How long will it take to completely eliminate the h allele?
  3. How would this change if the susceptible (h) allele is dominant?

 
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Posted by on April 28, 2014 in Education, Uncategorized

 

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