![]() ![]() EXAMPLE: For example, further experimental research may indicate the likelihood of the relationship being causal or not. This means that correlational analysis can identify relationships between variables which may open up new lines of research. (2) POINT: A further strength of a correlational analysis is that it can prompt further research to be conducted. EVALUATION:This is positive because it enables the researcher to compare and contrast results easily and gain a better understanding of the relationship between different variables. ![]() EXAMPLE:For example, a correlation co-efficient of 0.8 indicates a strong positive relationship between two variables whereas a co-efficient of 0.3 indicates a relatively weak positive relationship. This means that a correlational analysis is an effective way of measuring the strength of relationships between two variables. (1) POINT: A strength of using a correlational analysis is that it allows a researcher to view the strength of a relationship between 2 variables. (2) There will be a significant negative correlation between the amount of alcohol consumed and an individuals reaction times, the more units of alcohol consumed the slower reaction times in seconds will be.Įvaluation, AO3 of Correlational Analysis: (1) There will be a significant positive correlation between the amount of revision completed and the score obtained in an example, the more hours revision completed, the higher the score in an exam. there will be a significant positive correlation, negative correlation or, there will be no significant relationship). When writing a correlational hypothesis it is important that you state what you predict the relationship between the co-variables to be (e.g. Writing a Correlational Hypothesis Writing a hypothesis for a correlational analysis is very different to writing a hypothesis for a laboratory or field experiment. ![]()
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