Jargon & Basic Concepts

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Jargon & Basic Concepts. Howell Statistical Methods for Psychology. Questions. Define and illustrate: Population, Sample Parameter, Statistic Descriptive, inferential statistics Random selection (sampling), assignment Internal, External validity Discrete, continuous variables - PowerPoint PPT Presentation

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<ul><li><p>Jargon &amp; Basic ConceptsHowellStatistical Methods for Psychology</p></li><li><p>QuestionsDefine and illustrate:Population, SampleParameter, StatisticDescriptive, inferential statisticsRandom selection (sampling), assignmentInternal, External validityDiscrete, continuous variablesScale types (nominal, ordinal, interval, ratio)</p></li><li><p>Population vs. SamplePopulation collection of all the objects of interest to researcher (you). College students, students at USF Sample subset of objects from the population Want a representative sampleSamples are relatively practicalRandom samples have good propertiesOne persons sample is anothers population</p></li><li><p>Parameter vs. StatisticParameter numerical summary of populationE.g., mean, standard deviationStatistic numerical summary of sampleE.g., mean, standard deviationTypically we compute statistics and estimate parameters using statistics.</p></li><li><p>Descriptive vs. InferentialDescriptive statistics describe a sampleHow tall are these students?Inferential statistics use sample statistics to make decisions about populations.Is one method of instruction better than another?</p></li><li><p>Random Select &amp; AssignRandom selection is a process of picking a sample from a population so that each element has the same probability of being sampled.E.g., lottery, every 3rd name from a list (this is actually a systematic sample but its good)Random assignment is assignment to treatment so that each element has an equal probability of being assigned to each treatment.E.g., lottery, every other name, etc.Both are typically accomplished by lists (aka frames) and computer generated numbers (e.g., SAS PROC PLAN)</p></li><li><p>Internal, External ValidityInternal validity - quality of inferences about the study itself. Random assignment, history, maturation, etc.External validity quality of inferences from the study to the larger domain of interest. Representative sample of participants, task relevance, behavioral consequents, etc. Aka generalizability of the results (but not generalizability study). </p></li><li><p> Variable &amp; DistributionVariable vs. constantAttribute either varies across objects or notDistribution: Collection of dataDistribution: Array of scoresHeightBeck Depression IndexRat bar pressWonderlic</p></li><li><p>Discrete vs. ContinuousMathInteger vs. real numbersData Categorical vs. continuous (many valued, ordered)ExamplesPolitical party, job satisfaction, response time, country of origin</p></li><li><p>Scale typesNominal, ordinal, interval, ratioNominal categories. No ordering; mean has no connection to attributesOrdinal rank order onlyInterval rank order plus equal interval. ratio of differences has meaningRatio rank order, equal intervals, rational zero point. Ratio of numbers has meaning.</p></li><li><p>Scale Types: Footrace review</p><p>NominalOrdinalIntervalRatioID numberRank order of finishTime of day of finishElapsed time from start043110:57 a.m.4 min011210.59 a.m.6 min136311:01 a.m.8 min112411:02 a.m.9 min086511:04 a.m.11 min</p></li><li><p>ReviewFind a partner to work on this exercise.</p><p>Suppose you want to know whether one brand of tennis shoe is better than another. You have about $10K from a grant to study this. Describe a study you might conduct to find out. What might be your population, sample, independent and dependent variables? What statistics might you want to compute? Never mind the actual statistical test at this point. What data would you gather? What might a critic say about the internal and external validity of your study? What scale types are your IV and DV?</p><p>******</p></li></ul>