The acquistion of knowledge, throughout human history, is the result of interrogations of nature (mostly through experimentation, but sometimes through just thinking).

In turn, this dialogue with nature is done through measurements and hypothesis formation. This is a highly imperfect process as measurements are uncertain and error prone.

Thus, at any given time, our knowledge about any subject is highly incomplete.

Yet this vital aspect of how we learn and what we know is almost totally forgotten today. Today, knowledge is "facts" that you memorize and those "facts" are the answer - they are the truth.

As an example, most of you would simply rather memorize the table below rather than understand how it was constructed in the first place as well as the uncertainties involved.

Type	Color	Approximate Surface Temperature	Main Characteristics	Examples
O	Blue	> 25,000 K	Singly ionized helium lines either in emission or absorption. Strong ultraviolet continuum. No hydrogen lines; No calcium or sodium.	10 Lacertra
B	Blue	11,000 - 25,000	Neutral helium lines in absorption. Very week hydrogen lines	Rigel Spica
A	Blue	7,500 - 11,000	Hydrogen lines at maximum strength for A0 stars, decreasing thereafter.	Sirius Vega
F	Blue to White	6,000 - 7,500	Hydrogen lines are present but weaker than in A stars; Lines of Calcium start to be come strong as well as Sodium.	Canopus Procyon
G	White to Yellow	5,000 - 6,000	Solar-type spectra. Absorption lines of neutral metallic atoms and ions (e.g. once-ionized calcium) grow in strength.	Sun Capella
K	Orange to Red	3,500 - 5,000	Metallic lines dominate. Weak blue continuum. Sodium is very strong.	Arcturus Aldebaran
M	Red	< 3,500	Molecular bands of titanium oxide noticeable. Band heads are very "thick" abosrption lines that break up the spectrum.	Betelgeuse Antares

Subtypes

Individuals that confuse knowledge with "fact memorization" are unlikely to ever be able to solve problems because they have refused training in methodology. Knowledge is acquired through measurement . If you don't measure a phenomena, you can't learn about it. You can only be aware of its existence. This makes nature appear to be "magic". It's not - its physics.

The exercise that we did on tuesday will serve as the "template" or calibration for today's exercise where you will be able to apply what you measured to therefore determine the spectral types of unknown stars.

But first, back a bit to knowledge:

The soup is "knowledge soup" fluid, lumpy, with chunks that float in and out of awareness.

What you believe "science" to be is the process illustrated above that produces The Answer . Now that would be magic!

Instead, the process is more like the following:

A testable prediction is made which then adds to the soup of knowledge. Either the the theory is completely wrong, or its partically correct and we move on.

As long as we believe that the process exists only to produce an answer, we will never get anywhere! As long as we believe the only thing that matters is "the answer" we will never learn anything.

The key to science literacy (and the reason for this class) is to understand the vital role of measurements in constructing a knowledge pathway.

This brings us to the idea of calibration, or templates, or standards.

For instance, we can all identify what these objects are:

• Object 1
• Object 2
• Object 3
• Object 4

When classifying stars, you are doing the same thing. On Tuesday you made up the rule set for classifying stars, and soon you will apply it.

But none of us knows what this is . So how would we go about trying to figure it out? Look for the answer on the Internet?

Its stressful and difficult and uncertain to "determine things". The only tool we have available to us is measurement and guessing. Well that's what knowledge is!

And if your really actually stress out now, here is a stress test If you can see two dolphins, your not under stress.

But those are only qualitative rules that can use as a guide. On tuesday we built a quantitative template based on the 4 lines that were measured for different elements. To that table, which was constructed from your average measurements, I added one more line from Magnesium at 5175.

So now your template for identification or comparing against stars of unknown spectral type looks like this.

Once again, measure the strength of the features as you did on tuesday and fill out this table . When your done, compare your table with the template above and determine the spectral types of X1,X2,X3 and X4 (e.g. X2 is a K star (its not by the way))

And again, its easiest if you don't measure the whole spectrum at once. For instance 1) first set the plot limits to 3500 to 5000 (instead of the default values 3500 to 6500) and then measure the 4340,4472, and 3934 lines for X2,X2,X3,X4.

Then set the plot range from 5000 to 6500 and measure 5885 and 5175 for X1,X2,X3,X4.

If you use a background of no element (which you should) you can more easily see the blue reference line. Remember, bracket the feature between the green lines and move the blue reference line to just outside the green line boundaries. The numbers in the readout boxes in the lower right are what you enter. Compare those numbers in your table to the template table above to sleuth out what kind of star you just measured.

When your all done publish your results to global view.