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MATH 243 (6)
Lecture 5

MATH 243 Lecture 5: Sampling, Experiments, & Probability (Day 5)
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Department
Mathematics
Course
MATH 243
Professor
Bijan Shahir
Semester
Spring

Description
Sampling, Experiments, & Probability (Day 5) 4/17/17 - “Calendar” - Webwork 2 due M @ 5 pm - Friday: Webwork 3 & Excel - Chapt. 8: Sampling to Produce Data - Population = entire group of individuals - Sample = part of pop. which we sample - Sampling design = how we choose sample - Need to know - Pop. to describe - What to measure - Convenience sample = sample selected by taking members easiest to reach - Voluntary response sample = responders chose to respond themselves - Biased = design systematically favors one outcome - Simple random sample (SRS) = everyone has equal chance of being selected - Like drawing names from hat - No favoring - Better than convenience / voluntary sampling - Inference = drawing conclusions from pop. - A political scientist wants to know how college students feel about the Social Security system. She obtains a list of the 3,456 undergrads @ her college & mails questions to 250 students at random. Only 104 respond. - Sample = 104 - Only 1 college; not reputable - Chpt. 9: Experiments to Produce Data - Observational study = observes individuals but doesn’t attempt to influence responses - Experiment = deliberately imposes treatment on individuals - Confounded variables = 2 variables where response variables can’t be distinguished - Subjects = individuals in experiment - Factors = explanatory variables - Treatment = condition (specific) applied to subjects - Statistically significant = observed effect so large it would rarely occur by chance - Matched pairs design = compares 2 treatments - Chpt. 12: Probability Sampling, Experiments, & Probability (Day 5) 4/17/17 - Random = phenomenon has uncertain individual outcomes in large # of repetition - Probability = proportion of times outcome would occur in long series of repetition - Sample space = set of all possible outcomes - Event = outcome or set of outcomes
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