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Cal Poly STAT 217 - Logic of Statistical Inference

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Stat 217 – Day 4PreviouslyPreviously: Obs Units, VariablesExample 1: Butter side down?Example 2: Friend or FoeSlide 6Example 2: Possible explanations“Simulation”Need to repeat this processQuizFor TuesdayStat 217 – Day 4Logic of Statistical InferencePreviouslyLab 0: Interpreting probability as long-run relative frequencyWhat percentage of the time does the outcome happen over many, many trialsAlways refer to “lots and lots of trials” Always put your comments into context (What is being repeated? What is the outcome of interest?)Previously: Obs Units, VariablesA variable is a characteristic that varies from observational unit to observational unitVariables can be classified as categorical (a group designation) or quantitative (meaningful numerical value).The research question generally summarizes the variable or compares the variable across different groups.Can I say something about a larger group?Is there a genuine difference between the groups?Example 1: Butter side down?VideoSee longer version in PolyLearnExample 2: Friend or FoeExperiment 1Example 2: Friend or FoeWhat result (statistic) would convince you that these infants are generally more likely to pick the helper than the hinderer based on the videos?Example 2: Possible explanationsThese infants genuinely prefer the helper toyThese infants do not genuinely prefer the helper toy but we happened, by chance alone, to get a large majority picking the helper in our sample.We can investigate this second case…“Simulation”Instead of working with infants, we will assume the infants behave like a coin toss. Assuming same probability for each infantToss your coin 16 times, to represent the 16 identical infants, and record the number of headsWhat are the outcomes that “could have happened” when we know heads and tails are equally likely?What conclusion does this point to?Need to repeat this processWant to see the pattern of these results, the general trend to help us assess what results are typical and which we would consider surprisingIf our data (statistic) is atypical compared to these “could have been” results, then we will have evidence against the “by chance alone” explanation.QuizFor TuesdayReading 2Pre-Lab for Lab 1Turn in Investigation 1 at beginning of class in


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Cal Poly STAT 217 - Logic of Statistical Inference

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