Category Archives: How to Think Like a Scientist

Astronomy, How to Think Like a Scientist, Mac's Notebook

9. How to Think Like a Scientist – Astro Scale

Astronomy scale distances
Illustrators and designers have struggled with the best way to represent the Solar System graphically.

Imagine holding an automobile in your hand. It’s easy, just pick up a matchbox car. Matchbox cars have lots of features of a real car, just shrunk down. Scientists call this a “scale model.” Model because it is not a real car, and scale because all the parts are shrunk down by the same amount. A Matchbox car is scaled by about 1:64, meaning a real car is 64 times bigger than the toy.

thunderbird_matchboxA Barbie doll is also a scale model, but it can’t fit in the matchbox car because it is scaled differently. Barbie dolls are scaled by about 1:6. A real girl is about 6 times bigger than the doll. Barbie is over 10 times bigger than the matchbox car. For Barbie to drive a Matchbox car, the car would have to be about the size of a football, or she would have to be shrunk down to the size of penny.

Thinking like a scientist means trying to describe reality to make future predictions. A very effective way to do this is by using models. They help scientists understand things that are too humungously big (or small) or too freakazoidically far away to make sense of. But remember, for a model to make sense all objects in the model must be at the same scale. Barbies and Matchbox cars are both scale models, just not to the same scale.

Models are often mathematical, but can also be made of die-cast metal and plastic. The more accurate the model and the more closely it describes reality, the better. Some toy cars just roll. Others have working doors and make noise.

Definitely Not to Scale: Here is a real picture of a basketball and a real picture of a pea. Presented together, the pictures suggest something that anyone who has played basketball and eaten their vegetables knows to be untrue -- that they are roughly the same size. You'll notice that in scientific pictures, a ruler or some other object of known size is often included in the frame. Otherwise, it's very hard to know from a photograph how big something really is.
Definitely Not to Scale: Here is a real picture of a basketball and a real picture of a pea. Presented together, the pictures suggest something that anyone who has played basketball and eaten their vegetables knows to be untrue — that they are roughly the same size. You’ll notice that in scientific pictures, a ruler or some other object of known size is often included in the frame. Otherwise, it’s very hard to know from a photograph how big something really is. But of course, a ruler wouldn’t help much with objects of planetary size.

Consider our solar system: Our nearest star, the Sun, is big. Really big. 865,000 miles wide. 110 times wider than the Earth. But what does that mean? Let’s build a model.

Imagine the Sun was scaled down to the size of a basketball, how big would the Earth be? The size of a baseball? Of a golf ball? No. More like the size of a pea. A basketball and a pea.

To Scale, Sort of: In this picture, our basketball and our pea are presented in proper size relative to one another. Case closed? Not quite. Since this article is talking about models and has been discussing the earth and the sun in terms of peas and basketballs, this picture suggests that this is how the earth and sun would look together. It is, sort of, but for the model to work the pea would need to be much, much further away from the basketball, 94 times as far away, in fact. Many of the Solar System maps you see on posters show the planets and sun much closer together than they really are, even when the relative size differences are factored in.
To Scale, Sort of: In this picture, our basketball and our pea are presented in proper size relative to one another. Case closed? Not quite. Since this article is talking about models and has been discussing the earth and the sun in terms of peas and basketballs, this picture suggests that this is how the earth and sun would look together. It is, sort of, but for the model to work the pea would need to be much, much further away from the basketball, 94 times as far away, in fact. Many of the Solar System maps you see on posters show the planets and sun much closer together than they really are, even when the size differences are factored in.

The Sun is far away from us, 93 million miles away. But what does that mean? If the Sun was a basketball in the hoop of one basket at a basketball court, the Earth would be a pea at the other basket 94 feet away.

If we keep going, a quarter-mile away from the basketball Sun is a golf ball named Jupiter. A half-mile mile away is a pingpong ball called Saturn. Three-quarters of a miles away is a walnut named Neptune. The NASA spaceship Voyager 1 (the furthest out manmade object ever) is a speck of dust about a mile away from the basketball.

Perfect: We've created the most accurate picture yet! Only problem, it may be the world's most boring poster. (The yellow arrow helps you find the pea in this expansive field of blue. It's there - we promise). There is a reason they call it space.
Perfect: We’ve created the most accurate picture yet! Only problem, it may be the world’s most boring poster. (The yellow arrow helps you find the pea in this expansive field of blue. It’s there – we promise). There is a reason they call it space.
So the Sun is really big and far away But the other stars are so much farther away I can barely describe it. The Sun is just one of many stars in our Milky Way galaxy. One of the next closest stars is Alpha Centari over 26 trillion miles (4 light years away). But what does that mean? Let’s expand the model.

Suppose the Sun was a basketball was at Disneyworld, Orlando Florida, at the Space Mountain ride. At that scale, Alpha Centari would be another basketball at Space Mountain in Disneyland in Pasedena, California 2,500 miles away! And that’s just the closest star. Other stars in our galaxy are much farther away.

To make sense of them, we would have to change the scale of our model again. Shrink the Sun down to the size of a pea. Earth is the size of a poppy seed. Alpha Centauri is now a pea only a mile away still in Orlando Florida. Other stars in our Milky Way galaxy are peas in California. And that’s just our galaxy.

The next closest galaxy to the Milky Way is Andromeda. The Andromeda galaxy is 2 million light years away. What does that mean? We need another scale!

Stars are really far away. Musician George Hrab explained it best in his classic song, “Far.”

“I sense all the explosions going off inside your brain
As your mind gets blown by what I just did explain
Sorry if my words might drive you all insane
But that’s what happens when precision is your middle name

This stuff is far, [it’s really far] this stuff is far far far away
We’re talkin’ far, [like über far] you can’t get there by car in a day”

Talking Like a Scientist: Magnitude
Scientists have an easy tool to help make sense of really big numbers and make comparisons.. When looking at any two numbers, scientists count the number of digits in each number. For instance, with Barbie’s scale factor (the number of times it is shrunk), 64 has two digits a 6 and a 4. If two scale factors have the same number of digits (like 64 and 11), then scientists say they are of the same order of magnitude. If one scale has 2 digits and the other has 1 digits (like 64 and 6), the 64 is considered to be an order of magnitude smaller. Barbie dolls are an order of magnitude larger than a matchbox car.

Venus is closer to the Sun than Earth, but they are the same order of magnitude away. Andromeda is 6 orders of magnitude farther away from Earth than Alpha Centari.

References:

http://en.wikipedia.org/wiki/Matchbox_(brand)

http://www.eharm.net/night_sky_guide/distance_and_time/distance_and_time.html

Song, “Far” by George Hrab from the album Trebuchet.

Song “The Sun is a Mass of Incandescent Gas” – by They Might Be Giants, from the album Severe Tire Damage.

365DaysofAstronomy.org

How to Think Like a Scientist, Mac's Notebook

8. How to Think Like a Scientist — Following the Evidence

Nobel Prize-winning physicist and accomplished bongo player Richard Feynman, in the classroom.
Nobel Prize-winning physicist and accomplished bongo player Richard Feynman, in the classroom.

When he was a kid, my buddy Richard was smart enough to be afraid of dragonflies.  They had a wicked bite or sting or whatever.  They were dangerous and scary.  Every kid in his town knew this.  The flying terrors were even nicknamed “darning needles”.  When a dragonfly would buzz by during school recess, kids would scream and scatter away.  The same thing was true in my hometown.  My brother even played baseball with a guy who got bit or stung or whatever by a dragonfly and had to be taken to the hospital.

My friend Richard was afraid but also curious.  He wanted to know how bad these ‘darning needles’ really were.  Was it a bite?  A sting?  How painful?  Deadly?  What were the best tactics to stay safe?

He wasn’t a freakazoid, though.  He wasn’t crazy enough to want to experiment with them personally.  Instead, Richard researched the topic to learn what other scientists had found.

This was the days before Google searches and Wikipedia.  So Richard got a book about dragonflies and read all the facts.  Guess what he found?  Dragonflies don’t bite or sting; they are totally harmless!

So when a dragonfly landed on his foot at the beach that summer, he amazed everyone by casually observing the bug and not flinching.  The other kids were screaming and running away in terror, and Richard just stood there, as cool as an ice cube.  Richard was small for his age and not physically strong, but on that day he was the Big Man on the beach.

Thinking like a scientist, Richard followed the evidence he learned and changed his ideas about dragonflies.  To continue being scared after learning they were harmless would be just silly.

Everyone has ideas they believe to be true.  But good scientists are not afraid to follow the evidence wherever it leads.  It’s okay to experiment on your own, and even try a few times.  But if the evidence clearly contradicts your original position, a good scientist admits he’s wrong, and revises his position.   A bad or lazy scientist ignores evidence or make excuses and just keeps his old views.

It takes courage.  I’m sure that Richard was a little scared when that dragonfly first appeared at the beach.  But he trusted the facts he had learned.  Science is about making accurate predictions.  Accuracy comes from following the evidence.

Talking like a scientist, Richard did 5 important things:

  1. He had a hypothesis – “dragonflies are dangerous”
  2. He researched the topic, learning facts that others have already discovered
  3. He found evidence that falsified his hypothesis
  4. He revised his hypothesis – “dragonflies are dangerous harmless”
  5. He experimented, testing and confirming the new idea

My buddy Richard’s last name is Feynman.  I never met Richard Feynman but I call him a friend because he is one of my heroes.  He grew up to become a Nobel Prize winning physicist and accomplished bongo player. Learn more about him at http://www.feynman.com/

Fun Phineas Feynman Quote

“Nature doesn’t care how smart you are. You can still be wrong.” –Richard P. Feynman

How to Think Like a Scientist

7. How to Think Like a Scientist – Shaving the Truth with Occam’s Razor

William of Ockham (c. 1287 – 1347) was an English Franciscan friar and scholastic philosopher and theologian, who is believed to have been born in Ockham, a small village in Surrey. (William of Ockham, from stained glass window at a church in Surrey.)
William of Ockham (c. 1287 – 1347) was an English Franciscan friar and scholastic philosopher and theologian, who is believed to have been born in Ockham, a small village in Surrey. (William of Ockham, from stained glass window at a church in Surrey.)

As Mac would say, I’m a freakazoid.  I don’t put milk in my cereal.  Never.  But I love a cold glass of milk with my cereal. So having finished off the gallon last night with dessert, I was keenly aware that we were out of milk, and that this morning was going to start off badly.

Instead, when I awoke I was pleasantly surprised and a bit shocked to find a fresh gallon sitting in the fridge!  Where did it come from?  My pre-breakfast mind quickly came up with three possible answers to the presence of the mysterious milk jug.

  1. My wife got up early and picked up some groceries before going to work.  or…
  2. Burglars broke into my house and left behind a gallon of milk.  or…
  3. My wife bought a cow last night, stabled it in the garage, and milked the cow this morning.

Of course there are many more possible answers.  But these were my top three pre-breakfast guesses and all successfully explained the mystery milk.

Before doing any investigation, how do I choose?  Which answer should I prefer?  Talking like a scientist, “which one would be my working hypothesis?”  Fortunately science has a great tool to help.  It’s called Occam’s Razor.

Occam’s Razor is named after 14th century philosopher, William of Ockham, who argued that “simpler explanations are, other things being equal, generally better than more complex ones.”

razorHis razor blade shaves away details that are unnecessary.

Very often in science (and in life), there is more than one solution that can explain a mystery.  Occam’s Razor picks the simplest solution, until there is a need for more accuracy.  The principle allows you to quickly decide where to focus your efforts.

In my case, scenario 1 is the simplest answer.  My wife bought some milk this morning.  This may be wrong.  But until I hear mooing coming from the garage, or see a newspaper headline about “Burglar Bandits Leave Milk Behind”, this is my working hypothesis.

Your math teacher would use the Razor if a student claimed that space zombies stole his homework.  Occam’s Razor would suggest that maybe the student just forgot to do the assignment.

Remember, Occam’s Razor is a guide. not a judge.  Start simple, and only add complications when you need to explain additional observations.  It may turn out that space zombies did steal the kid’s homework.   And I may have a cow in my garage.  I’ll go check after breakfast.

Illustration Credit: Razor detail from linen texture postcard, Boston Public Library. “Since 1731, J.A. Henckels Twin Brand Razors and Shears, radiant with quality and beauty like the rising sun, have been recognized by the discriminating master barbers as the best the world produces and the most satisfactory and the most economical to use.” Harry H. Baumann, 216 W. 18th Street, New York.1930 – 1945 (approximate)

How to Think Like a Scientist

6. How to Think Like a Scientist – The Custard Effect

How to think like a scientist for kidsCustard makes me puke. Violently. Specifically, chocolate custard. It’s my working hypothesis. I only have two data points, but that’s enough for me. Talking like a scientist, chocolate custard causes me to puke. The effect of me eating chocolate custard is: me puking. The arrow of cause ==> effect is one way. My need to puke did not cause me to eat chocolate custard.

Cause and effect. Every scientist studies causes and effects. The cause happens first, and then later there is an effect. Always. It’s so obvious that at times we forget. Cutting onions make me cry. Onions cause me to cry. The effect of cutting up onions is crying. And crying does not cause me to cut onions.

But, when I cut onions, I also always listen to the radio. These two things happen in pairs, but are completely unrelated.

This leads to one of the most important parts about thinking like a scientist: just because things happen together, does not mean that one necessarily caused the other, or that they are even related. Talking like a scientist, if things happen together it is called “correlation”. The biggest mistake people make is when they assume correlation also means causation. There is a correlation between the onions and listening to the radio, but there is no causation.

My favorite football team wins when I wear my lucky T-shirt. Did me wearing my “lucky T-shirt” cause (or even help) my team to win? Probably not. It’s more likely that I often wear that shirt on game days, and my team wins a lot. Correlation does not mean causation,

But sometimes it’s hard to know what’s going on. Thinking like a scientist, I observe:

Every night my dog barks at midnight.

How does my dog know its midnight? She even adjusts for daylight savings time! Is it magic? Does the clock cause my dog to bark?

No! After further investigation, it turns out that she barks every night at midnight because that’s when my neighbor lets his dog outside. Midnight and my dog barking have a correlation. But the cause of the barking is my neighbor’s dog. The time of night had nothing to do with it.

But sometimes it’s hard to know what causes what.

Suppose you find that all the kids who wear glasses also sit in the front row of your class. Does sitting up close cause their eye problems? Or are they sitting up close because they have eye problems?

The great thing about noticing correlations is that it leads to ideas for new hypotheses and experiments. The experiments will provide evidence either supporting causation or falsify the idea.

For instance, I could ask my neighbor to let his dog out at 10pm to see if my dog will bark early. Or I could do custard flavor experiments. Maybe I only puke on chocolate custard and I will love strawberry custard…

Fun Phineas Effect Facts
One of the most common grammar mistakes in the English language is confusing the words ‘effect’ and ‘affect’. Wow your English teachers by never mixing them up.

Effect with an E is a noun, meaning ” the result of”. What was the effect of me eating chocolate custard? Puke.

Affect with an A is a verb meaning “to influence or change”. Verbs are action words. Remember: A for action. Bad weather affects my mood. So does puking.

How to Think Like a Scientist

5. How to Think Like a Scientist – Controlling the Chocolate Chip Experiment

phineas_scientist001So I learned how to make my mother’s delicious chocolate chip cookies. But after a few batches I got bored, and like a scientist, started to experiment. My mom didn’t enjoy walnuts and rarely baked with them, but I love them. I decided to change her recipe and add walnuts to my mix. Success! My roommates and I thought they tasted great (except for my friend Tony, who is allergic to nuts).

But were the cookies better than the original recipe? It was hard to know. It was hard to remember exactly how the originals tasted. So, thinking like a scientist, the next time I divided the cookie dough into two bowls and added walnuts only to one of them. I baked both batches and we did a taste test. The walnut chocolate chip cookies were clearly superior. And Tony was happy.

Talking like a scientist, the batch of original recipe cookies was the control group and the walnut batch was test group. The original ingredients are called dependent variables and the walnuts the independent variable.

The mark of a good experiment is that it is a controlled experiment with only one independent variable. You only want to change one thing at a time so you know what you are testing. The control allows you to compare the results of the change.

It is fine to do an uncontrolled experiment (like I did with my first attempt at walnut cookies). But if the results are good, it should be followed by a controlled experiment to verify them.

Scientists use uncontrolled experiments to generate ideas for new hypotheses. Hey, what if I throw in some jalapeño peppers into the cookie dough?

Fun Phineas Fact
In medical research, controlled experiments are called clinical trials. Over the years, it has been shown that the results are more accurate if the patients don’t know whether they are in the control group or the test group. We call these blinded trials.

Think about doing a soda pop taste test with your friends. Then try it again putting a blindfold on them before they drink. Blinding prevents personal opinions from altering results.

It has been found that results are even more accurate when the doctors and nurses running the experiment don’t know which group is the control. We call these double blinded trials. A double blinded controlled trial is difficult and expensive to run, but is the gold standard of medical research.

The US Food & Drug Administration requires double blinded clinical trials be run before approving new medications.