L5 QUASI

• used to establish relationships among pre-existing behaviors and used to predict one set of behaviors from others

  correlational designs
• show relationships between sets of antecedent conditions and behavioral effects but the antecedents are preexisting

  correlational designs
• neither manipulated nor controlled by the researcher

  correlational designs
• path analysis and cross-lagged panel designs

  advanced correlational methods
• used to propose cause-and-effect relationships by developing causal models

  advanced correlational methods
• seeming like

  quasi
• often seem like real experiments but they lack one or more of the essential elements such as manipulation of antecedents or random assignment to treatment conditions

  quasi-experimental design
• subjects are selected for the different conditions of the study on the basis of preexisting characteristics

  quasi-experimental design
• used to compare behavioral differences associated with different types subjects, naturally occurring situations or wide range of common or unusual events

  quasi-experiments
• experimenters can use this whenever subjects cannot be assigned at random to receive different experimental manipulations or treatments

  quasi-experimental designs
• common in nonexperimental studies that is discussed as a research method in its own right

  correlation
• designed to determine the correlation or degree of relationship between 2 traits, behaviors or events

  correlational study
• when 2 things are correlated

  changes in one are associated with changes in another
• used by researchers to explore behaviors that are not yet well understood

  correlational study
• any observable behavior , characteristics, or event that can vary

  variable
• selected traits or behaviors of interest are measured first

  correlational study
• statistical technique for summarizing data that could be used in studies falling in any portion of our graphic scheme

  correlation
• researcher measures events without attempting to alter the antecedent conditions in any way

  correlational study
• once the correlation is known, it can be used to make __

  predictions
• the higher the correlation, the more ___ our prediction will be

  accurate
• relationships between pairs of scores from each subject

  simple correlation
• most commonly used procedure for calculating simple correlations

  Peason Product Moment Correlation Coefficient (r)
• 3 general outcomes in Pearson r

  positive relationship

  negative relationship

  no relationship
• values of a correlation coefficient can only range between ___

  -1.00 to +1.00
• visual representations of the scores belonging to each subject of the study

  scatterplots
• often the first step of the researcher towards analyzing correlational data

  scatterplots
• lines drawn on scatterplots

  regression line / lines of best fit
• describes the linear relationship between 2 measured scores

  regression line
• direction of the line corresponds to the ___ of the relationship

  direction
• computed value of r is positive, the more a person watches tv, the larger his vocabulary

  positive correlation
• also called a direct relationship

  positive correlation
• when r is negative, the more person watches tv, the smaller his vocabulary

  negative correlation
• the direction of the relationship (positive or negative) ___ affect our ability to predict scores

  does not
• r is near zero, prediction may be no more accurate than any random guess, we would not learn anything about a person's vocabulary thru knowledge of tv habits

  no relationship
• features of data that can affect correlation coefficient

  nonlinear trend

  range truncation

  outliers
• imposition of units, artificial restriction of the range values of X and Y

  range truncation
• cannot be adequately captured by simple correlations, the rs would be very small or even zero because the data do not have a simple, straight-line relationship

  curvilinear data patterns
• extreme scores

  outliers
• can dramatically reduce the size of the correlation coefficient because it disturbs the general linear trend of the data

  outliers
• even a ___ does not indicate a causal relationship

  perfect correlation