CHYS 3P15 - Lecture Notes.docx

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Department
Child and Youth Studies
Course
CHYS 3P15
Professor
Heather Lawford
Semester
Winter

Description
Lecture Notes Hypothesis testing not an exact scienceBased on data you seeSteps in hypothesis testing1Develop nullalternative hypothesis2Set alpha3Calculate power to determine sample size4Collect data5Collect statistic and pvalue6Accept or reject the null Sampling distribution of meansSampling distribution is a frequency distribution of a sample statistic Distribution of sample means is usually referred to as the sampling distribution of means or the sampling distribution of the mean Develop two hypothesesAll hypotheses test are comprised of 2 mutually exclusive hypothesis No difference between control and experimentalNull both means come from the same populationoAny difference between the means is due to chanceNull controlexperimentaloThis is the hypothesis that you are able to testoIf the null hypothesis is probably not true what must we conclude AlternativeoNo direction hypothesis 2tailedcontrolexperimentalodirectional hypothesis 1 tailedexperimentalcontrolcant test this hypothesis directly but can find support by rejecting the null hypothesis We cannot just look at means and determine if they differremember random errorstatistical fluctuations in the measured data random error is always presentWhy are means differentThe means are different because of random error ie any difference is due to chance this is the null hypothesisMeans are from two different populations ie There is a true difference between the means alternative hypothesisIn any situation we can never know the truth but we can calculate the probability that any difference are due to chance pvalue Set the alphacut off probability to reject the nullConventionally alpha005 or 5There is only a 5 probability that the difference is due to chance then we reject the nullCollect dataCalculate statistic and pvalue associated with the testCompare the pvalue to the alphaMake decisionoReject the null if palphaoFail to reject the null if palphaStatistics does not mean you have to be certainRejectFail to rejectNull is Type 1Right choice p 1 truealphaNull is Right choice Type 2falsePowerEffect sizeJust because a difference is significant doesnt mean its bigRefers to how large the difference between your variables Greater effect sizegreater similaritiesPower probability that we will reject the null when there is a significant difference If we reject the nullincreases confidence that our study can detect a difference when its thereOr if fail to rejectincreases confidence that its due to insufficient power to detect the effects Assuming its there how powerful does the telescope power need to bePower to detect your size telescopeWhat size of effect are you trying to detect objectSample size to detect effect size magnifyLots of random error if its cloudyIndependent ttestsDifference in means that we observe between 2 groups more than we would expect to see based on chance aloneTtest 1 dependent variable and 1 independent variable containing 2 groupsEffect SizeIs only relevant when effect is significant Pvalue is not a good indicator of relationship sizeStrength of the effect size measure is that it provides the strength of the relationshipResults are statistically significant if palphaStandard deviationAverage amount of scores differ from the mean Add all scores andbyof observationsZscoresStandardization of scoresObservations expressed in standard deviation units from the mean
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