PSY3213C Research Methods in Psychology Exam 2 Study Guide Chapters 6 9 Chapter 6 Surveys and Observations Describing What People Do Recognize the strengths weaknesses associated with different question formats on surveys E g open ended forced choice etc What is a Likert Type Scale The individual answers a question by selecting a response alternative from a designated scale anchors the labeled opposite extremes and sometimes middle especially if it is to represent neutral no set rules for labeling but exact point labeling reduces ambiguity What is the advantage of exact point labeling instead of using two anchors on a scale Reduces ambiguity What is a response set and what are ways that you can design a survey to reduce the likelihood of it tendency for participants to answer all or most of the questions the same way whenever questions in a series all have the same choices for responding researchers can take away the neutral option to reduce the likely hood of fence sitting What is socially desirable responding and how can you reduce it What is an implicit measure when the participant responds based on what they think the researcher wants to hear An implicit measure is computerized measures to evaluate people s implicit opinions about sensitive topics Be able to recognize different examples of observer bias intellectual bloomers versus normal kids maze bright versus maze dull o Besides bias what other concerns must people take into consideration when conducting observational data collection observing people ethically training observers well and using clear rating scales use multiple observers and assess in rater reliability Chapter 7 Sampling Estimating the Frequency of Behaviors Beliefs What is the difference between a sample and a population Understand the importance of both randomization and reducing bias in selecting a sample Sample The group selected to represent the population Population The complete set of individuals or events that we want to represent Random sample is deal and not often met Biased samples are not representative or contains too many people compared to the population of interest Be able to differentiate between the different types of both random and nonrandom sampling o stratified vs proportionate stratified is used to obtain a diverse sample the population is divided into demographic strata then a random sample of a fixed size is drawn from each stratum proportionate is like stratified but the proportions of different groups in the population are reflected in the samples from the strata o random sampling with vs without replacement without replacement refers to if a member chosen from a population cannot be selected again after being returned to population with replacement a member is eligible to be selected to be selected once returned to the population snowball ask participants to recruit others o convenience sample vs snowball sample convenience available and willing o cluster divide population of interest into clusters the randomly sample from each o multistage like cluster but you take a random sample from each cluster not o systematic using computers or a random number table to sample everyone in each cluster Chapter 8 Bivariate Correlational Research Be able to identify if a Pearson s correlation coefficient r is being correctly or incorrectly used to evaluate a correlation i e are the two variables both on an interval or ratio scale Interval or ratio data only How do r values help determine an effect size Can an effect size be large even in cases with small r coefficients Magnitude of r tells you the strength of LINEAR relationship between variables 10 small weak 30 medium moderate 50 large strong Would a bar graph or a scatterplot be more appropriate to examine data when one of your variables is measured on a nominal categorical scale scatter plots because they show the degree and pattern of the relationship between the two variables Understand p values as they related to statistical significance as well as what a p value less than 05 means How does it relate to the probability that your results were caused by random error Statistically significant p 05 there is a less than 5 chance that we found this relation by chance and that it does not exist in the population Nonsignificant p 05 there is a greater than 5 chance that we found this relation by chance and that it does not exist in the population How can looking at subgroups help explain unusual scatterplot results Subgroups can cause issues because sometimes when you have an association between two variables the apparent over all association is spurious meaning that the overall relationship is attributable only to systematic mean differences on subgroups within the sample What is the affect of an outlier on a correlation Outliers can be problematic for an association claim because even though they are only one or two data points they may exert disproportionate influence Understand why correlations cannot establish causation temporal precedence third variable problem etc In order to have causation You must have Convariation of the cause variable and the effect variable There must be correlation or association between the cause and the effect Temporal Precedence The causal variable HAS to come FIRST in time before the effect variable Internal Validity There must be NO plausible alternative explanation for the relationship When you take those three things and put them up against most correlations you will not be able to meet those three criteria why we would call it correlation o When is a third variable a moderator A third variable that depending on its level changes the relationship between two other variables Understand the relationships between correlation and regression How are r and R2 related What is the line of least squares The relationship between memory score and achievement is statistically significant relationship r How much variance in achievement scores is explained by memory variance r 2 Line of the least squares The line that makes the sum of the squares of the vertical distances of the data points from the line as small as possible Chapter 9 Multivariate Correlational Research How can longitudinal data be combined with correlational data to help examine potential causal relationships Longitudinal Data Can help establish temporal Precedence It measures the same variable multiple times across time days months years o What is the difference between cross sectional correlations
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