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# FLOW CHART.pdf

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Michael Rochon

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) μ ) p2 p ) ˆ − 2 2 p 2 ( n -p Case 2 ⎞ ⎟⎟ ⎠ p − n p2 2 ⎞⎟ ⎟ ⎠ 1 1 2 −1 21 + ) n p )1 estimate estimpte ) + (p + p to to 1 Chapter 13 Z test & p2 1 1 ) ) 2 − n1 2 ⎞⎟ ⎠ p Nominal − ⎛ ⎜⎜ ⎝ 2 ˆ & (1 σ W estimator of p p p p 1 1 p Size // Size / ( − 2 2 − − n 2 z W zα Case 1 x n p1 11 Case α ⎛⎜ ⎝ ⎛⎜ ⎜ ⎝ p1 + ++ ( p z = = x nn1 for ) F > F ala,1VSamplen, V2,Sample n = ˆ2 = ˆ − 2s2 n2 z p z ˆ1 + Estimator For a For a one t2i1ed1negative test ( μ2 n2 n −2 < − ⎞ ⎟⎟ ⎠2 2 2s2 n estimator oLCL UCL F F F 1 2s n 2 s ( ( + + 2 + D D ) 21 1 n1 1 1 Interval D s n x2 ⎛ ⎜⎜ ⎝2 1 n −1 μ 2 − ( 2s1 n D D / 1 ( μ n tα 2 ( = Pairst- test & / ± -1 = Matchhed D D D μ tt d.f. estimator of x 2 2 = = ) PROOBJECTIVE Type of Descriptive Measurement t t t- test & − 2 − est(Unequal variances) Central Location Unequal variance2 1n+ ) ) 1 ≠ − n Experimental Design? 1 known? or 2 ( σ - = ( μ1 2 S ⎞ ⎟⎟2⎠ ) 1 n ˆp Are (Perform F-test) )2 + ) − n YES Population Variances t- test & μ ⎞ ⎟⎟ ⎠ 1 n p ( nddepenndenntt Samples Equal variances − 1 2 ⎛2 p ⎝ p − n ˆp estimator ofriances) s ˆ ( 2 − + 1 / z test &p p α 2 1 2s n )2 ⎛ ⎜⎜ ⎝ t Nomminall z Chapte2 12 ) , 1 / 2s x 2sp ± estima=or of p ± σ − 2/ − − 1 2 −1 2 z p n χ n 2χ − σ ( − ( ( n = 1 2test& = = ( Chapter 12 tt ( χ = estimator of 2 Data Type LCL UCL χ μ2 μ -1 s n μ Variability μ n 2 Describe a Single Population − s α t- test & t = ± z-test & estimattr of x Intervall estimator of μ n Measurement known? μ σ Type of Descriptiveocation − σ n / Is YES NO x zα z- test & = ± estimatzr of x Chapter 10 & 11 Chapter 12 μ p 2 ) ⎟ ⎟ ⎠ estimate esttpate to2 to ( ⎞ ⎟ ⎠ p W ) Size/ Size /
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