Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.
1 Page
Document Preview
Time # [days] Mag Magerr Band Uplim Ref 0.00124 21 -0.2 White yes GCN6442 0.00124 20.3 -0.2 White yes GCN6442 0.00124 19.5 -0.2 White yes GCN6425 0.00247 20.1 -0.2 V yes GCN6442 0.04334 20.5 -0.2 UWM2 yes GCN6442 0.04572 -0.2 19.9...
Unformatted Document Excerpt
Coursehero >> California >> Berkeley >> ASTRO 00279898Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Time # [days] Mag Magerr Band Uplim Ref
0.00124 21 -0.2 ...
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more.
Course Hero has millions of course specific materials providing students with the best way to expand
their education.
Below is a small sample set of documents:
Below is a small sample set of documents:
Berkeley - ASTRO - 00279898
4.0400000 61.610001 7.1451508 -0.41814225 1001.9206 61.610001 118.12200 20.627281 -3.6769901 354.82811 118.12200 165.84300 0.85697829 0.46365326 2.1961292
Berkeley - ASTRO - 00279898
chi^2/nu= 583.53516 / 530The fit is rejectable at 94.655339 % Confidence -1.13500 -0.125000 673.21980 -0.125000 1.89500 596.91803 1.89500 2.90500 543.74160 2.90500 4.9250
Berkeley - ASTRO - 00279898
<html><head><title>Your NED Search Results</title></head><body background="/pics/NEDbgHelp.gif" bgcolor="#FFFFFF"><center><font size=6 color="#CC3333"><b>N</b></font><font size=4 color="#000000"><b>ASA/IPAC</b></font>&nbsp;<font size=6 color="#CC
Berkeley - ASTRO - 00279898
105.331 105.647 31.9371 10.6457105.647 105.983 35.2344 11.1667105.983 106.54 21.2545 6.73612106.54 107.255 30.6725 7.04795107.255 107.874 16.3039 5.43463107.874 108.324 26.3083 8.33782108.324 108.999 17.5389 5.55854108.999 110.047 20.9264 4.80
Berkeley - ASTRO - 00279898
#ra dec hmag dhmag121.761492 57.373802 16.583 0.109121.839149 57.362671 15.934 0.072121.845650 57.362106 16.563 0.119121.878377 57.374729 16.787 0.143121.919215 57.368423 16.790 0.140121.946543 57.365799 14.985 0.037122.014110 57.370487
Berkeley - ASTRO - 00279898
;instrument XRT;exposure 28866.189;xunit kev;bintype counts 0.0000000 0.0049999999 13.962264 1.00000 0.0049999999 0.0099999998 14.012087 1.00000 0.0099999998 0.015000000 14.061908 1.0
Berkeley - ASTRO - 00279898
;instrument XRT;exposure 290.92548;xunit kev;bintype counts 0.0000000 0.0049999999 14.418612 1.00000 0.0049999999 0.0099999998 14.470081 1.00000 0.0099999998 0.015000000 14.521550 1.0
Berkeley - ASTRO - 00279898
#ra dec rmag drmag121.92242457.39402518.2130.022121.62311857.36968516.4630.005122.11588157.37616616.4370.005121.74430057.36147318.7580.037121.45689757.35495618.8740.041121.94667757.36584617.3990.011121.68458557.35956517.582
Berkeley - ASTRO - 00279898
chi^2/nu= 46.341148 / 1010.00The fit is rejectable at 0.0000000 % Confidence#index t1 t2 fade_index delta_mag_pk hindex dhindex rate1 drate1 rate2 drate2 logr dlogr 0 0.1053 0.1107 -5.49 -1.2 -0.02 2.53 1.37E+0
Berkeley - ASTRO - 00279898
# t1 t2 hardness error 0.10533100 0.10654000 0.033205765 0.18595095 0.10654000 0.10787400 -0.47071013 0.17014860 0.10787400 0.11004700 -0.13664215 0.15874708 0.11004700 0.11150900
Berkeley - ASTRO - 00279898
output00279898000_999/sw00279898000xpcw2po_cl.evtoutput00279898002_999/sw00279898002xpcw2po_cl.evtoutput00279898003_999/sw00279898003xpcw2po_cl.evtoutput00279898004_999/sw00279898004xpcw2po_cl.evt
Berkeley - ASTRO - 00279898
# t1 t2 dt rad_min rad_max cts err scl bg bg_rat wt 0.105331 0.105647 0.000316 0. 16. 9.00 3.00 0.891786 0.000000 0.442367 1 0.105647 0.105983 0.000336 0. 16. 10.56
Berkeley - ASTRO - 00279898
# t1 t2 dt rad_min rad_max cts err scl bg bg_rat wt 0.105331 0.105647 0.000316 0. 16. 9.00 3.00 0.891786 0.000000 0.442367 1 0.105647 0.105983 0.000336 0. 16. 10.56
Berkeley - ASTRO - 00279898
#ra dec rmag drmag 122.043490 57.242304 22.240 0.166 122.042753 57.243598 20.562 0.039 122.046058 57.245232 21.425 0.081 122.038653 57.246476 21.855 0.118 122.050433 57.247262 22.647 0.239 122.054296 57.248938
Berkeley - ASTRO - 00279898
# tmin tmax 0.390447 362.94357 [ksec];instrument XRT;exposure 28199.801;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.00000
Berkeley - ASTRO - 00279898
# tmin tmax 0.390447 362.94357 [ksec];instrument XRT;exposure 28199.801;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.00000
Berkeley - ASTRO - 00279898
# tmin tmax 0.105331 9.52529 [ksec];instrument XRT;exposure 290.59126;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.000000 0
Berkeley - ASTRO - 00279898
# tmin tmax 0.105331 9.52529 [ksec];instrument XRT;exposure 290.59126;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.000000 0
Berkeley - ASTRO - 00279898
Wavdetect Sources with S/N>3: # ra dec err ["] signif counts steady? -log10(Prob_steady) 0121.87930057.6087600.49623.2102.2 10.0 1122.04476757.5588570.43820.684.2 10.0 2121.71746357.5594740.56313.138.9 10.0 3121.8245
Berkeley - ASTRO - 00279898
SIMPLE = T / file does conform to FITS standardBITPIX = 8 / number of bits per data pixelNAXIS = 0 / number of data axesEXTEND = T / FITS dataset may contain extensio
Berkeley - ASTRO - 00279898
# Ep dEp lprob lEiso dlEiso367.029 0.299 -5.82e-05 -9.923 0.133367.349 0.343 9.37e-04 -9.923 0.130367.716 0.392 -2.07e-04 -9.923 0.130368.136 0.449 1.56e-03 -9.923 0.130368.617 0.514 1.21e-03 -9.923 0.130369.168 0.589 -9.47e-05 -9.923 0.130369
Berkeley - ASTRO - 00279898
# Ep lEiso84.630 -11.03993.335 -11.069105.169 -10.742111.295 -10.729113.642 -10.812116.762 -10.893118.703 -10.621120.415 -10.557123.044 -10.845123.148 -10.840125.002 -10.729128.219 -10.757129.407 -10.608131.558 -10.664133.038 -10.7181
Berkeley - ASTRO - 00279898
# Ep dEp lprob lNiso dlNiso367.029 0.299 -5.82e-05 6.012 0.171367.349 0.343 -5.26e-04 6.012 0.172367.716 0.392 -2.74e-04 6.012 0.172368.136 0.449 1.19e-03 6.012 0.172368.617 0.514 -5.11e-04 6.012 0.171369.168 0.589 -7.77e-04 6.012 0.171369.798
Berkeley - ASTRO - 00279898
# Ep lNiso84.656 5.79493.377 5.598105.180 6.148111.307 6.058113.647 5.829116.768 5.600118.709 6.198120.422 6.325123.051 5.733123.155 5.640125.010 5.872128.228 5.767129.416 6.096131.564 5.943133.044 6.102133.655 5.579136.309 5.912136
Berkeley - ASTRO - 00279898
Spectra Extracted from tstart=-12.245 tstop=106.935(Trigger Time, GPS=863718307.260000, Redshift, z=0.0)Power-Law Model FitNorm@15keV 3.4685e-03 (2.5014e-03 4.6091e-03)alpha -1.1303 (-1.3449 -0.9112)Energy Fluence (15-350 keV) 2.4807e-06 (2.15
Berkeley - ASTRO - 00279898
#file=swb15-350lc.txt dt=1.0 tstart=-5.175 tstop=31.185#t90 dt90 t50 dt50 rt90 drt90 rt50 drt50 rt45 drt45 tav dtav tmax dtmax trise dtrise tfall dtfall cts cts_err pk_rate dpk_rate band 35.000 4.368 14.000 4.386 16.000 2
Berkeley - ASTRO - 00279898
# S/N T1 T2 T90 T50# Estimated T100 Interval: -12.245 106.935 T90= 96.960 14.6 -4.165 97.845 92.920 47.470
Berkeley - ASTRO - 00279898
# tmin tmax 10.0000 362.94357 [ksec];instrument XRT;exposure 25279.347;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.00000
Berkeley - ASTRO - 00279898
;instrument XRT;exposure 25765.123;xunit kev;bintype counts 0.0000000 0.0049999999 13.998108 1.00000 0.0049999999 0.0099999998 14.048058 1.00000 0.0099999998 0.015000000 14.098007 1.0
Berkeley - ASTRO - 00279898
# tmin tmax 10.0000 362.94357 [ksec];instrument XRT;exposure 25279.347;xunit kev;bintype counts0.000000 0.010000 0.000000 0.0000000.010000 0.020000 0.000000 0.0000000.020000 0.030000 0.000000 0.0000000.030000 0.040000 0.00000
Iowa State - CI - 501
C I 501 Reading Reflections Lily Compton September 16, 2002 1. What is the meaning of systems approach to instructional development? Instructional development is a "problem-solving process, which requires the identification of instructional problems
N. Georgia - HEHOLB - 0679
Ms. Holbrook World History ClassMultimedia Research Project RubricStudent Name:_ Topic:_ Date:_ Research Process: Gathered information from journals, books, CDs, and the Internet Resources are current and reliable Extracted, synthesized, and applie
N. Georgia - HEHOLB - 0679
Fun Fishy CountStudent Activity Sheet * Teacher or Paraprofessional: read questions to students and help them find answers as they play the game. Name: _ 1. What color was the shark 2. Write the word: How many sea horses 3. What color was the crab ?
N. Georgia - HEHOLB - 0679
Hayley HolbrookCSCISeptember 20 2005Grade Analysis100.00 90.00 80.00 70.00 60.00 50.00 Column G 40.00 30.00 20.00 10.00 0.00 Lauren Edwards Patrick Johnson Tony Pirkle Amanda Stokes David Yates Megan Brown Thomas Jekins Tabitha Lawson Josh Sco
N. Georgia - HEHOLB - 0679
Written Description of the Project for the StudentsOver five days you will learn about the senses of the body. You will be split into five groups of five students each. On the first day each group will learn about a different center where they will
N. Georgia - HEHOLB - 0679
Group Members: _Katie Caldwell, Carissa Camp, Haley Holbrook, Brenda Newman, Ryan Sasscer_Group Project Lesson PlanLesson Plan Title: Developed by: Subject Area: Grade Level: Purpose of the Activity: Our Five Senses Katie Caldwell, Carissa Camp, H
N. Georgia - HEHOLB - 0679
The Five Senses Grading Rubric Teachers: Ms. Holbrook, Ms. Camp, Ms. Caldwell, Mr. Sasser, and Mrs. Newman Student Name: _ Grade: _ CATEGORY Participation 4 Used time well and focused on the activity. 3 Used time pretty well. Stayed focused on the a
N. Georgia - HEHOLB - 0679
Using this website answer the following questions. http:/www.kidshealth.org/kid/body/tongue_SW.html 1. What part of your body helps you to taste?_ 2. True or False? Your tongue is one large muscle. _ 3. Could you ever swallow your tongue? Why or why
N. Georgia - HEHOLB - 0679
Group Participation Sheet Name:1. Do you feel that your group worked well together today? Did you work as a team?2. Did everyone in your group participate? Did everyone in your group comment or share their ideas? 3. On a scale of 15 how much
N. Georgia - HEHOLB - 0679
25 Useful Web Sties for Education http:/www.bravenet.com- This website has many different tools that would be useful to make a web site, such as free audio and free clipart. http:/www.4teachers.org This website helps to integrate te
Wisconsin - WEB - 710
Econ 710: Discussion #7Naoya Sueishi March 6, 20091Omitted and Irrelevant VariablesTake the homoskedastic model yi = x1i 1 + x2i 2 + ei E(e2 |x1i, x2i) = 2 i E(x2i|x1i) = x1i = 0. E(ei|x1i, x2i) = 0Example 1: (Midterm 2004)Suppose the pa
Wisconsin - WEB - 709
Econ 709: Discussion #4Naoya SueishiOctober 3, 20081Joint Distribution and IndependenceLet (X, Y ) be a random 2-vector with the following pdf: fX,Y (x, y) = 8xy if 0 x y 1 0 otherwise.Example 1:1. Are X and Y independent? Can we use
Wisconsin - WEB - 710
Econ 710: Discussion #7Naoya Sueishi March 6, 2009Example 1: (Midterm 2004) I hope my answer is correct. If you find any mistakes, please let me know. Define ui = x2i - x1i . Then x2i = x1i + ui E[ui|x1i] = 0. So, we obtain yi = x1i1 + x2i 2 + ei
Wisconsin - WEB - 709
Econ 709: Discussion #3Naoya SueishiSeptember 26, 2008Result 0.1 The expected value of a random variable g(X) is E[g(X)] = provided E|g(X)| < . Properties of expectation: 1. E[aX + b] = aE[X] + b. 2. E[X + Y ] = E[X] + E[Y ]. 3. If X() 0 for a
Wisconsin - WEB - 710
Econ 710: Discussion #1Naoya SueishiJanuary 23, 200911.1Matrix algebraLinear DependenceLet a1 , a2 , . . . , ak be a set of vectors. The vectors are said to be linearly dependent if there exists a set of scalars (c1 , c2, . . . , ck ), no
Wisconsin - WEB - 710
Econ 710: Discussion #8Naoya SueishiMarch 27, 20091BootstrapTn = Tn (X1 , . . . , Xn )Let X1 , X2, . . . , Xn be iid from F . Letbe a statistic. The exact CDF of Tn is Gn (u, F ) = P (Tn u|F ). If Gn (u, F ) does not depend on F (Tn is
Wisconsin - WEB - 710
Econ 710: Discussion #9Naoya Sueishi April 3, 20091Confidence intervals^ ^ d 1. Asymptotic Distribution: Suppose ( - )/s() N (0, 1). Let z be the 'th quantile of the standard normal distribution. An asymptotic (1 - )% confidence intereval for
Wisconsin - WEB - 709
Econ 709: Discussion #4Naoya SueishiOctober 3, 2008Example 4: Suppose that X1 and X2 are independent and both have the standard normal pdf. What is the pdf of Y = X1 /X2 ? Answer. We use the result of Example 3. We have fY (y) = = = = =z2 y2 z
Wisconsin - WEB - 710
Econ 710: Discussion #13Naoya Sueishi May 1, 20091ReviewThe model is yi = x1i 1 + x2i 2 + ei E[xi ei ] = 0Example 1: (Final 2006)where x2i R. You want to test H0 : 2 = 0 H1 : 2 = 0. Describe how to test H0 using the nonparametric bootstr
Wisconsin - WEB - 710
Econ 710: Discussion #10Naoya Sueishi April 10, 20091GMMyi = xi + ei E[zi ei ] = 0.Take the modelThe efficient GMM estimator for is ^ -1 ^ -1 ^ GM M = (X Z Z X)-1 X Z Z y. ^ where is a consistent estimator of = E[zi z i e2 ]. i Speci
Wisconsin - WEB - 710
Econ 710: Discussion #3Naoya SueishiFebruary 6, 20091t tests and confidence intervals^ ^ Let = h() : Rk R be a parameter of interest, its estimate and s() its asymptotic standard error. Consider testing H0 : = 0 versus H1 : = 0 . The s
Wisconsin - WEB - 709
Econ 709: Discussion #5Naoya SueishiOctober 10, 20081Moment Generating Functions tx - e fX (x)dx tx xX e fX (x)The moment generating function, denoted by MX (t), is MX (t) = if X is continuous if X is discrete.Theorem 1.1 If MGFs exist (
Wisconsin - WEB - 710
Econ 710: Discussion #2Naoya SueishiJanuary 30, 20091Projection MatrixLet X be a n k matrix with rank(X) = k. The matrix P = X(X X)-1 X is called projection matrix. The projection matrix has the following properties: 1. P is symmetric and
Wisconsin - WEB - 709
Econ 709: Discussion #6Naoya SueishiOctober 17, 2008Example 2:Let X1 , X2, . . . be i.i.d. from Uniform[0, 1].1. What's the distribution of X(1,n) min1in Xi? (Provide the cdf.) 2. X(1,n) . What's the numerical value of ? Use the definitio
Wisconsin - WEB - 710
Econ 710: Discussion #12Naoya Sueishi April 24, 20091Time series1. IID: et mutually independent and identically distributed. 2. Martingale difference sequence (MDS): E[et|It-1 ] = 0. 3. White noise: E[et] = 0, E[etes ] = 0 for t = s.Time ser
Wisconsin - WEB - 710
Econ 710: Discussion #6Naoya SueishiFebruary 27, 20091Generalized (Weighted) Least Squares EstimatorsThe model is yi = xi + ei , E(ei|xi) = 0.Example 1: (Midterm 2001)An econometrician is worried about the impact of some unusually large