Textbook Notes (368,317)
Psychology (9,695)
PSYB01H3 (581)
Chapter 13

# Chapter 13.docx

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Department
Psychology
Course
PSYB01H3
Professor
Connie Boudens
Semester
Fall

Description
Chapter 13Inferential statistics allows researchers to assess how confident they are that their results reflect what is true in the larger population and assess the likelihood that their findings would still occur if their study was repeated over and over againSAMPLES AND POPULATIONInferential statistics is necessary because the results of a given study are based on a single sample researchers rarely study the whole populationTherefore inferential statistics are used to determine whether the results match what would happen if we were to conduct the experiment again with multiple different sets of sample NULL AND RESEARCH HYPOTHESISStatistical inference begins with a statement of null hypothesis and a research hypothesisNULL HYPOTHESIS simply states that the population means are equal and any difference noticed is simply due to random errorRSEARCH HYPOTHESIS the population means are not equal and that the independent variable DID have an effectIf we can determine that the null hypothesis is incorrect then we accept that the research hypothesis is correct which means that we accept that the independent variable did have an effect on the dependent variableWe can only reject a null hypothesis when the probability that the obtained results could be due to random error is very lowSTATISTICAL SIGNIFICANE a significant result is one that has a very low probability of occurring if the population means are equal PROBABILITY AND SAMPLING DISTRIBUTIONSProbability the likelihood of occurrence of some event or outcomePROBABILITY THE CASE OF ESP o The probability required for significance is called the alpha level o The most commonly used one is 005 and the outcome of the study is considered to be significant when there is 005 or less probability of obtaining the results which basically means that there is 5 or less chance of the differences being due to random errorsSAMPLING DISTRIBUTIONS o The sampling distribution is based on the assumption that the null hypothesis is true o When the obtained data is very unlikely according to the null hypothesis expectations then you infer that the differences arent just due to random errorSAMPLE SIZE o The bigger the sample size and the more the number of observations the more likely you are to obtain an accurate estimate of the true population valueEXAMPLE THE t AND F TESTSThe t test is commonly used to examine whether 2 groups are significantly different from each otherThe F test is used to determine whether there is difference between 3 or more groupst TEST o If the obtained t value has a low probability 005 or less then the null hypothesis is rejected T group difference within group variabilityT
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