Class Notes (807,158)
York University (33,498)
Yogi (1)
Lecture

# Ch 10-13

2 Pages
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School
York University
Department
Course
Professor
Yogi
Semester
Winter

Description
Chapter 10 Statistical Inferences acquires infodraw conclusion about population samples Estimation value of population parameter of sample statistic Sample mean xand estimate population mean2Types of estimator 1 Point Estimator value of unknown parameter using SINGLE VALUE do not reflect larger sample size or parameter value 2 Interval Estimator confidence interval RANGE OF VALUE unknown parameter using intervalslowerupper confidence limit w level of confidence Qualities of Estimators unbiased consistency relative efficiency Unbiased estimator expected value is equal to parameter Excant tell how close to parameter Consist estimator difference btwn estimatorparameter grows smaller as sample gets larger Relative Efficient estimator 2 unbiased 1 variance smaller is relative efficient larger confident level produces wider confidence intervals larger value ofproduce wider confidence intervals larger sample size narrow confidence interval interval too wideincrease sample sizeChapter 11 Nonstatistical Hypothesis 1 Null Hypothesis Ho goes against what trying to prove ex defendant innocent 2 Alternative research Hypothesis H1 trying to prove something ex defendant guilty Type 1
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