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Correlational Research in psychology
Correlational Research
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Institution
Correlational Research in psychology
Research in psychology relies on two primary categories of methodologies. One of the categories is correlational research, and the other one is experimental. Each of these two categories plays a significant role in research and is responsible for providing various aspects. Variables are the key differentiating aspects between the two categories in a research. Correlational research involves using statistics to determine the relationship between the involved variables (Schmidt, n.d.). Firstly, the research methodology involves identifying hypothesis and theories that two available variables are connected. In turn, this makes correlational study a quantitative research. The next step involves scrutinizing and grouping each of the variables with an aim of separating them. At this stage, researchers find as many details as possible about the subject under investigation. This is done using varying methods depending on the required information about a subject. Observation, for example, is a method that researchers apply in gathering information under correlational research. Taking surveys and handing out questionnaires are other methodologies that researchers apply in acquiring new information related to the subjects under scrutiny. Researchers also explore archived information about a subject with an aim of unraveling new information about the subject in a study.
Correlational research involves two variables that have a link. In this case, aggressiveness and performance are two variables that have a relationship. Aggressiveness is a variable that can relate to someone’s performance at work. In addition, it is an aspect in life that is easily triggered by different factors. These factors include life’s challenges where one has to be aggressive to overcome hurdles in life. Additionally, aggression can be triggered by goals in life. Just like hard work, aggression is a necessary ingredient required to attain great success in life (Waters, 2013). Therefore, aggression is easily brought out in a person by the urge to make a big achievement. As such, research of aggression can be based on a noticeable factor such as a life goal. Performance is something that workers strive to achieve at their places of work. They work with diligence as they look forward to impressing their employers and possibly attaining rewards. Performance is a factor that can be measured using different methods. For example, it is possible to quantify it by the number of products one processes within a defined period. The two variables presented in this case can be identified by making critical observations, which is one of the methodologies applied in correlational research.
Results obtained upon carrying out a study on one’s performance at work based on personal aggression can lead to several changes. The results can be used in various ways, but more importantly to improve the work place functionality. Often, employers aim at improving productivity at the place of work and they do that by checking their employees’ performance. Hence, the results attained from studying employees’ performance and aggression can be used to formulate means of improving productivity. Employers can coin triggers that can help employees achieve the required level of aggression. Such triggers include placing incentives, achievable deadlines, and workloads. Consequently, employees work with a mindset that they need to complete projects within the expected standards to attain the incentives set aside for them (Waters, 2013). Employers can use the results to know the areas in a workplace that need adjustments. However, some areas may be performing as expected while some may be in need of improvement.
References
Schmidt, R. S. (n.d.). Correlational research. Research methods. Retrieved on 20 September 2013 from http://capone.mtsu.edu/sschmidt/methods/correlational.html
Waters, J. (2013). Conducting correlational research. Capilano University. Retrieved on 20 September 2013 from http://www.capilanou.ca/psychology/student-resources/research-guidelines/Correlational-Research-Guidelines/
Correlation and Regression
Correlation and Regression
Author
Institution
Regression describes a statistical technique that helps to measure the association between a dependent variable and independent variable (s). Given dependent and independent variables, regression measures the direction and rate of change of one variable to the other. Therefore, through regression, it is possible to predict the value of dependent variable using the independent variables; the predictor and criterion variables help in determining the cause and effect association. On the other hand, correlation measures the closeness of the association between variables. It indicates the degree of association between variables (Jain, 2009).
The two statistical methods are similar in that they measure relationship aspects amid variables. Regression measures the direction of an association between variables while correlation measures the degree of association between variables (Jain, 2009). Besides, the two are similar in that they make use of available variables; without the use of these variables, the statistical methods cannot come up with the relationship aspects between variables.
On the other hand, there are some differences between the two statistical approaches. In regression, there must exist an independent variable and dependent variable (s) while in determining correlation, there is no need of having dependent and independent variables; the analysis does not involve the use of fixed and dependent variables. Correlation does not assume cause and effect association between two variables always. Although variables may high correlation, it does not imply one variable is the effect while the other is the effect. However, regression always expresses cause and effect association amid two variables (Jain, 2009). Besides, regression helps in making prediction while correlation does not aid in making any prediction between variables. Therefore, regression analysis will be preferred to correlation in researches involving cause and effect relationships.
References
Jain, T.R. (2009). Quantitative Method for MBA. New York: FK Publications.
Correlation and Regression with SPSS
Correlation and Regression with SPSS
Statistical assumptions for the study
The difference is zero
The data is normally distributed
The variance of the two variables are equal (homoscedasticity)
The study wishes to analyze the correlation that exists between education and affirmative action. During the study, t-test will be used for hypothesis testing. The independent variable is education while affirmative action is the dependent variable. During the study regression analysis will also be used. The regression line takes the following form:
Y= Bo + BX + e……whereY is the dependent variable (affirmative action), Bo is the constant, X is the independent variable (education) and finally e is the error term.
Hypothesis Statement
Ho: there is no relationship between education and affirmative action.
Ha: there is relationship between grade in elementary and high school and affirmative action.
In hypothesis testing we shall use the SPSS results found in Anova tables. The level of significance is 0.05. The p-value is 0.127 with 29 degrees of freedom.
The p-value (0.127)>0.05. Therefore we reject the null hypothesis but accept the alternative hypothesis. Therefore we conclude that there is a relationship between grade in elementary and high school and affirmative action.
Results
Regression
Y= -20.600 +0.67X + e
Interpretation of the regression at 95% confidence level
(-20.600) is the constant of the regression line. The coefficient of the independent variable (education) is given by 0.67. This means that; holding other factors constant, an increase in the level of education by one unit will raise the level of affirmative action by 0.67.
Correlation coefficients
Using Pearson correlation from the SPSS output, the coefficient between highest grade in elementary or high school and affirmative action is 0.67. This is a strong positive correlation; meaning that they both move in the same direction. Increasing grade in elementary and high school will result to a positive increase in affirmative action.