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WGU RFC 1 ch 8
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WGU RFC 1 ch 8
Summary of Chapter 8
Question  Answer 

Correlational research  involves collecting data to determine whether and to what degree a relations exists between two or more variables 
degree of relation  is expressed as correlation coefficient 
If two variables are related  scores within a certain range on one variable are associated with scores within a certain range on the other variable 
Relation between variables  does not imply that one is the cause of the other 
not infer causal relations  on the basis of data from a correlational study 
correlational studies  may be designed either to determine whether and how a set of variables are related or to test hypotheses regarding expected relations. 
Variables to be correlated  should be selected on the basis of some rationale suggested by theory or experience 
common, minimally accepted sample size for a correlational study  30 participants 
variables correlated have low reliabilities and validities  a bigger sample is necessary 
Basic correlational design, scores for two (or more) variables of interest  are obtained for each member of a selected sample, and the paired scores are correlated. 
A correlation coefficient is a decimal number between  1.00 and +1.00. It describes both the size and direction of the relation between two variables 
If correlation coefficient is near  .00, the variables are not related 
A correlation coefficient is near  +1.00 indicates that the variables are strongly and positively related. An increase on one variable is associated with an increase on the other 
If the correlation coefficient is near  1.00, the variables are strongly and negatively or inversely related. An increase on one variable is associated with a decrease on the other variable 
Correlations of +1.00 and 1.00  represent the same strength but different directions of relation 
A correlation coefficient much lower than .50 is  generally not useful for group prediction or individual prediction. 
However a combination of correlations below .50  may yield useful prediction 
Coefficients in the .60s and .70s  are usually considered adequate for group prediction purposes 
Coefficients in the .80s and higher  are adequate for individual prediction purposes 
Common variance or share variance  indicates the extent to which variables vary in a systematic way 
the higher the common variance  the higher the correlation 
Statistical significance  refers to the probability that the study results (e.g., correlation coefficient of this size) would have occurred simply due to chance 
Small samples require  larger correlation coefficients to achieve significance 
the value of the correlation coefficient needed for significance  increases as the level of confidence increases 
A low coefficient represents  a low degree of association between variables, regardless of statistical significance 
relationship study  conducted to gain insight into the variables or factors that are related to a complex variable, such as academic achievement, motivation, or self concept 
in a relationship study, the researcher  first identifies the variables to be related 
Prediction study  is an attempt to determine which of a number of variables are most highly related to the criterion variable 
Prediction studies  are often conducted to facilitate decision making about individuals or to aid in the selection of individuals. 
Variable used to predict  predictor 
variable that is predicted is  complex variable, called the criterion 
Data analysis in prediction studies  involve correlating each predictor variable with the criterion variable 
prediction study using multiple variables  results in a prediction equation referred to as a multiple regression equation, which combines all variables that individually predict the criterion to make more accurate prediction. 
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Xyrarose