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B01 CH13.pdf

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Anna Nagy

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Chapter 13understanding research results statistical inferenceInferential statistics are important whether the results yielded in one experiment will come out again if the study was repeated over and over again Samples and populationsInferential statistics are necessary because the results of a given study are based on data from a single sampleInferential statistics answers the questions would these results hold up if the experiment were conducted repeatedly each time with a new sampleInferential statistics are used todetermine whether we can in fact make statements that the results reflect what would happen if we were to conduct the experiment again and again with multiple samples o Can we infer that the difference in the sample reflects a true difference in the population Inferential statisticsIn the experimental design the groups are equivalent in every way except the independent variable manipulation o Equivalent groups are also achieved by randomization so that all other variables are controlled forThe difference between two groups will almost never be zero o This happens because we are dealing with samples rather than populations o Random or chance error is responsible for some of the difference in the means even if the independent variable had no effect on the dependent variableThe difference in sample means reflects any true difference in population means plus any random errorBy using inferential statistics we can make inferences about the true difference in the population on the basis of the sample data o Inferential statistics gives the probability that the difference between means reflects random error rather than a real difference Null and research hypothesesNull hypothesis the population means are equalthe observed difference is due to random error o The logic if we can determine that the null hypothesis is incorrect then we accept the research hypothesis as correctAccepting the research hypothesis means the independent variable did have a effect o The null hypothesis is rejected only when there is a low probability that the obtained results could be due to a random errorResearch hypothesispopulation means are not equalStatistical significance a significant result is one that has a very low probability of occurring if the population means are equal o Significance indicates that there is a low probability that the diference between the obtained sample means was due to random error o Matter of probability Probability and sampling distributionsProbability is the likelihood of the occurrence of some event or outcomeIn statistical inference we want to specify the probability that an eventwill occur if these no difference in the population
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