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STAT 2040 (125)
Lecture 8

# STAT 2040 Lecture 8: Lecture #8 Statistics Premium

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School
Department
Statistics
Course
STAT 2040
Professor
Jeremy Balka
Semester
Winter

Description
confiden tervals feb 13 inter procedures types of s confiden itives tests ple dat values for ue of sample upant estimate. an estimate of ue that pare Adence tence for p comtidence inter val ever create stactistT CanAicience level: pronahiny the intervine cateufa Meed uitl capture tru value of parameter (most common a 2.2. -Interval Estimaton of Au when known to con struct Canfidence intervee for mean, pop Start Sample mean add /Subtract the f erro error Assumptions I. Sauple data must be a s rand OLA pop uation of terest is2. p be norma lua distributed deriving as lo confidence lewe intervale for M inlet UZ. represent standard normal r.v. then pc-i.aesz as gle q le yendpoint hese neral, a (I-ok), loo confiden intervue for M hese 2. value of standard name a 3 Quantity of error bound on error error bound max. eni f eestimase Interval 2.2 nterpretati that tr nt,dence inter Sele of tte retarded sau method calculated using n of error A tectng 2. Factors factors affectina of errot standard dewiat 2. sa ple size. confi cienue reater mangan of error greater s tf error does not feet marznA of error. barevder confidence level greater of S. S 2.3 Confidence Intervals M When 8.3 introdue-ion quantHy nclosely related to standard mal distr outr t O bell-shaped. bs more area in trails alower peak dag ree 3 of freed (df) as in creases distribution end t evd stenaard nomme distrbuti SE (X) appropriate SE (X) standard error of X of confiden tervals feb 13 inter procedures types of s confiden itives tests ple dat values for ue of sample upant estimate. an estimate of ue that pare Adence tence for p comtidence inter val ever create stactistT CanAicience level: pronahiny the intervine cateufa Meed uitl capture tru value of parameter (most common a 2.2. -Interval Estimaton of Au when known to con struct Canfidence intervee for mean, pop Start Sample mean add /Subtract the f erro error Assumptions I. Sauple data must be a s rand OLA pop uation of terest is2. p be norma lua distributed deriving as lo confidence lewe intervale for M inlet UZ. represent standard normal r.v. then pc-i.aesz as gle q le yendpoint hese neral, a (I-ok), loo confiden intervue for M hese 2. value of standard name a 3 Quantity of error bound on error error bound max. eni f eestimase Interval 2.2 nterpretati that tr nt,dence inter Sele of tte retarded sau method calculated using n of error A tectng 2. Factors fact
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