UCR SOC 005 STAT SPR 2010 Session 19 V4

UCR SOC 005 STAT - SOCIOLOGY005 STATISTICALANALYSIS Session19 Monday,10May2010 DavidSwanson Watkins1223 [email protected] Institute for

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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Session 19 Monday, 10 May 2010 David Swanson Watkins 1223 [email protected] SOCIOLOGY 005  STATISTICAL ANALYSIS
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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Confidence Intervals, Part 2 Description of Mid-Term Exam
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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Confidence Intervals An ‘after-the-sample-is-taken’  SUMMARY  measurement based on   sample error used to guide decision- making under conditions of  uncertainty, due to sampling*
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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Confidence Interval Example:  Kitsap County Voter Poll*   95 % C.I.  Percent “yes” to Open-Space    Bond By how Much Tax One Would Pay                 $10             78.7  -   86.7                 $25             77.2  -   85.6                 $50             72.5  -   81.7                 $75             57.1  -   68.3                 $100           52.7  -   64.3 * Sample mean = 82.7, standard error (se) = 1.99
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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Normal Curve Formula P(X) =     {1/((2 Πσ 2 ) (.5) )} {e (-(X-μ) 2 /(2 σ 2 )) } (1) You only need to know the mean ( μ)  and the standard  deviation ( ) σ  of a set of numbers  to create the curve (2)  in inferential statistics, one substitutes the sample mean     ( )  for the population mean ( μ)  and the sample’s        standard error (se) for the population       standard deviation ( ) σ
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THE UNIVERSITY OF CALIFORNIA RIVERSIDE The University of   Mississippi Institute for Advanced Education in Geospatial Science Standard Error The Standard Error  is a value computed from a sample that  represents an estimate of the standard deviation of the  sampling distribution associated with an infinite number of  samples of the same size of the sample in question. This is the  key  measure in inferential statistics and represents not only  a  major assumption underlying all inference, whether in the form  of a confidence interval or a hypothesis test, but also the link  between the empirical sample and the theoretical mathematics  underlying statistical inference The Standard Error is computed by dividing the standard 
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This note was uploaded on 10/16/2010 for the course SOC 5 taught by Professor Burke during the Spring '08 term at UC Riverside.

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UCR SOC 005 STAT - SOCIOLOGY005 STATISTICALANALYSIS Session19 Monday,10May2010 DavidSwanson Watkins1223 [email protected] Institute for

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