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Conclusion

Take another look at the query you used to get your first 1,000 quasars:


select top 1000
objid, modelmag_u, modelmag_g, modelmag_r, modelmag_i, modelmag_z,z

from
SpecPhoto

where
specclass=3 and zconf > .95

The query you used limits the objects it returns by applying one "constraint" - the query returns only objects with zconf > .95. Zconf is a measure of the statistical confidence level in the redshift measurement. The query only returns quasars for which we are more than 95% certain that the measured redshift is correct.

Try modifying the query. A couple of ideas would be to change or eliminate the confidence level zconf, or to search for objects called "high-redshift quasars" as well. Or you could try searching for various lines in the quasars' spectra.

Launch the SQL search tool

To learn more about how to work with SQL, see SkyServer's Searching for Data how-to tutorial.

When you are dealing with a large database such as the SDSS (over 80 million objects in Data Release 1, and probably hundreds of millions when the survey is finished), you need to use tools such as the SQL Search tool to find the data you want.

Research Challenge. Modify the query slightly to obtain a different set of data. For example, look at only quasars with poorly measured redshifts (set zconf < some number). Maybe you want to look at very red quasars by setting the i and z magnitudes larger than a certain number. You could also search for very blue quasars using a similar technique.

Think of a question about quasars that you want to answer, and modify the query to get the data that will let you answer that question. Analyze the data using a spreadsheet, then draw conclusions about the quasars. When you finish your analysis, E-mail us your queries, your results, and your conclusions. We'll look over all the results we receive, and we'll put the best of them up on this web site!

If you need help with Structured Query Language, see SkyServer's Searching for Data tutorial, or do a web search for SQL. For other tutorials on SQL, see here and here.

 

Project designed by Robert Sparks

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