Chapter 12 - Testing for relationships. After reading this chapter, you should be able to: Explain the difference between tests of differences and tests of relationships, use the four analytical steps to design and interpret research designs and statistical findings, know which assumptions of inferential statistics your research project meets and which assumptions it does not meet,. | Chapter 12 Testing for Relationships Tests of linear relationships Correlation 2 continuous level variables Regression 2 or more continuous level variables Identifies statistically significant linear patterns in the association of variables Basic Assumptions Data collected from sample to draw conclusion about population Data from normally distributed population Appropriate variables are selected to be tested using theoretical models Participants randomly selected Alternative and Null Hypotheses Inferential statistics test the likelihood that the alternative hypothesis is true and the null hypothesis is not Significance level of .05 is generally the criterion for this decision If p .05, then alternative hypothesis accepted If p > .05, then null hypothesis is retained Four Analytical Steps Statistical test determines if a relationship exists Examine results to determine if the relationship found is the one predicted Is the relationship significant? Evaluate the process and | Chapter 12 Testing for Relationships Tests of linear relationships Correlation 2 continuous level variables Regression 2 or more continuous level variables Identifies statistically significant linear patterns in the association of variables Basic Assumptions Data collected from sample to draw conclusion about population Data from normally distributed population Appropriate variables are selected to be tested using theoretical models Participants randomly selected Alternative and Null Hypotheses Inferential statistics test the likelihood that the alternative hypothesis is true and the null hypothesis is not Significance level of .05 is generally the criterion for this decision If p .05, then alternative hypothesis accepted If p > .05, then null hypothesis is retained Four Analytical Steps Statistical test determines if a relationship exists Examine results to determine if the relationship found is the one predicted Is the relationship significant? Evaluate the process and procedures of collecting data Correlation Also known as Pearson product-moment correlation coefficient Represented by r Correlation reveals one of the following: Scores on both variables increase or decrease Scores on one variable increase while scores on the other variable decrease There is no pattern or relationship Correlation Correlation coefficient or r reveals the degree to which two continuous level variables are related Participants provide measures of two variables If r is .05, then the relationship is significant –hypothesis or research question accepted Correlation cannot necessarily determine causation X causes Y Y causes X Third variable causes both Interpreting the Coefficient Direction of relationship Positive- both variables increase or both variables decrease Negative – one variable increases while the other decreases Relationship strength < .20 – slight, almost negligible . – low, definite but small . – moderate, substantial . – high;
