Let's look at the properties of Abell 2065.  The cluster's sky position is

(RA,Dec) = (230.62156, +27.70763)

where both coordinates are given in decimal degrees.

Go to SDSS Skyserver: http://skyserver.sdss.org/ and under "Data Access" click on Navigate.

Go to Navigate, and put in the cluster coordinates. Click "Search".  Hopefully you'll see a cluster.

If you click on "Grid" (in Drawing Options), you'll get a scale bar which helps you work out the angular scale of the image. You can zoom in and out using the magnifying class +/- buttons, and you can pan by click-dragging.

Click on a galaxy. Over to the right, you'll see the galaxy in a little zoomed-in window, with the ugriz magnitudes given above it. If you click the "Explore" button underneath the zoom window, a new webpage will open up with more detailed properties of the galaxy, including (if it exists) a spectrum.

If you go back to the Navigate page, and (under Drawing Options) click "Objects with Spectra", it will highlight all sources that have spectroscopy, and you can click on one of them, click on Explore again, and you will see both photometry and spectroscopy data.

Play around. Scroll, zoom, click on galaxies and hit "Explore", etc. Look at a few spectra of galaxies in the field. Work out the following:

OK, so now you have a feel for the cluster, lets get some data and try and work out some quantitative analysis.

Instructions for downloading data
Jupyter notebook to get you started on analysis

Try a few of these things:

(Note: when I say plot "this" versus "that", "this" goes on the y-axis and "that" goes on the x-axis. So "plot color versus magnitude" means that color goes on the y-axis and magnitude goes on the x-axis.)

Advanced exercises to try:

Plotting and Slicing tips

want=(SDSS['g']<20) # for selecting objects with a g mag brighter than 20
want=(np.abs(SDSS['redshift']-0.1)<0.05) # for selecting objects in the redshift range 0.005 to 0.015
want=(SDSS['modelMagErr_r']<0.2) # for selecting objects with an r magnitude uncertainty less than 0.2
followed by, for example,
scatter(SDSS['r'], SDSS['g']-SDSS['r'], s=1) # if you want to plot the whole sample
scatter(SDSS['r'][want], SDSS['g'][want]-SDSS['r'][want], s=20,color='red')
# to then overplot the subsample
want=SDSS['g']<18 # bright
want=np.logical_and(want, SDSS['g']-SDSS['r']>0.7) # red
want=np.logical_and(want, SDSS['redshift'] != -999)
# has redshift

which would give you a "want" selection that is bright red galaxies with measured redshifts