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Chapter 6Surveys- Survey- series of self- report measures through an interview or written questionnaire, mostly widely used with group of people, snap shot of opinions or attitudes- Interviews- type of survey, helps interview grasp persono Unstructured- talks freely about many topicso Focus group- type of unstructured interview, o Structured- easier to compare, objective- Questionnaire- cheaper, without supervision, filled out, fixed formatSampling and Generalization- Census- measure each person about whom we wish to know- Probability sampling- each person has the same chance of being selected in the sample- Simple random sampling- each person has equal chance to be selected must first have a sampling frame of all people- Systematic random sampling- take every 70th if you know list is random- Strata- samples from subgroups of variables (done by stratified sampling)o Proportionate stratified sample- frames of all the people with each strata located, then random samples drawno Disproportionate stratified sample- when strata differ in size and researcher is interested in comparing characteristics of the strata- Oversampling- including a larger population then is actually represented in the population- Cluster sampling- break population into smaller groups for which there are sampling frames, then choose some clusters to include in sample- Sampling bias- not actually representative of population- Snowball sampling- contact homeless from homelessSummarizing the Sample Data- Frequency distribution- table that indicates how many (what percentage) of individuals in the sample fall into each set of categories, can be a bar chart- Grouped frequency distribution- combine adjacent variables into a set of categories and examine frequencies of each category- Histogram- bar chart with touching bars, indicates variable is quantitative- Frequency curve- frequencies of groups indicated with a line- Stem and leaf plot- original values can be seen- Distribution- pattern of scores observed on a measured variable- Normal distribution- shaped like a bell- Median- used instead of mean when distribution is skewed- Mean deviation- score on the variable minus the mean- Sum of squares- mean deviations squared and summed- Variance- sum of squares/ n = s^2- Standard deviation- sqrt (s^2)=s- Confidence interval- certainty that a population value is likely to follow in an area- Margin of error- confidence interval calledChapter 7Naturalistic Research- Naturalistic research- describes and measures the behavior of people/ animal as it occurs in everyday lives, must be organized into meaningful measured variables- Ecological validity- extent to which research is conducted in situations similar to everyday life experiencesObservational Research- Observational research- making observations of behavior and recording in an objective manner- Unacknowledged participant- can get close to people being observed, may have difficulty remaining objective, will people ever be told?- Acknowledged participant- may have to get permission, can get reactivity, but canalso be treated as a real member- Acknowledged and unacknowledged observers- does not want to be part of the group, may be more objective, more time to do job, unacknowledged can be unethicalCase Studies- Case studies- descriptive records of one or more individuals experiences and behavior, problem- based on experience of only a limited number or unusual individuals, cannot usually tell us about larger population, or reasons why it occurredSystematic Coding Measures- Systematic observation- specifying ahead of time which observations are to be made on which people, what time, what place- Behavioral categories- based on predictions of what would occur for children and what behaviors would be coded- Event sampling- focusing on specific behaviors theoretically related to social comparison- Individual sampling- observers randomly selected ne child to be the focus child for that observational period- Time sampling- each observer focused on a single child for 4 minutes before moving on to another caseArchival Research- Archival research- based on an analysis of any type of existing records of public behavior- Content analysis- same as systematic coding of observational data and specification of coding categories and use of more than one raterChapter 8Hypothesis Testing- Develop research hypothesis- Set alpha (a=.05)- Calculate power to determine the needed sample size- Collect data- Calculate statistic and p-value- Compare p-value to alpha (.05)o If p <.05, reject null, statistically significanto If p>.05, fail to reject null, statistically nonsignificant- Inferential statistics- using sample data to draw inferences about true state of affairsSampling Distributions and Hypothesis Testing- Sampling distribution- distribution of all possible values of a statistic- Binomial distribution- sampling distribution for events that have two equally likely possibilities - Sampling distributions become narrower as sample size gets bigger, as size increases- extreme values of the statistic are less likely to be observed- Null hypothesis- observed data is what’s under the normal distribution, expected on basis of chance- Alpha- significance level, normally set to .05, observed data must meet this in order to reject the nullo Smaller the alpha, more stringent the standard is- P-value- probability value, the likelihood of an observed statistic occurring on the basis of the sampling distribution- Two sided p-values- take into consideration that unusual outcomes may occur in more than one way Reduction of Inferential Errors- Type 1 errors- when we reject the null when we shouldn’t have because the null iscorrect, probability of the researcher making a type 1 error= alpha- Type 2 errors- not rejecting the null when we should have, because null is not correct, =beta, type 2 errors are more common when power is low- Power- probability that the researcher will be able to reject the null hypothesis given that it is false and should be rejected, power=1-beta- Effect size- indicates the magnitude of a relationship, 0 (none) to larger stronger relationships- When alpha is set lower, beta will be higherStatistical Significance and the Effect Size- Statistical significance= effect size x sample size- Increasing sample size will increase statistical significance- P-value is influenced by sample size- Effect size is an index of the strength of a relationship that is not influenced by sample size-


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UMD PSYC 300 - Chapter 6

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