Upon assessing the correlation coefficient of the bivariate correlation, it can be concluded that there is a weak relationship between the two variables. Furthermore, it is clear that there is a positive correlation between A and B and it is statistically significant. In addition, the coefficient of determination is 1.44 percent.
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A person unfamiliar with statistics should be presented to the concept of correlations and its key characteristics. Correlation can be defined as “a statistical technique that is used to measure and describe the relationship between two variables” (Gravetter & Wallnau, 2014, p. 450).
A numerical value of a correlation coefficient r can vary from 0 to 1, where 0 is indicative of the absence of a relationship between the two values. Given that r is close to 0, it can be concluded that a weak relationship is present. The positive sign of the r shows that there is a positive direction of the relationship. It means that when A variable increases, the B variable also increases and vice versa. It should be noted that there is no connection between a correlation’s sign and its strength.
A statistical significance p of a correlation can help to determine whether results can be attributed to random factors (Triola, 2015). By comparing p to 0.05, it is possible to tell whether a probability of obtaining r is higher or lower than 5 out of 100 cases. Taking into consideration the fact that p is 0.01, r can be obtained by chance only in 1 out of 100 cases, which means that the correlation is statistically meaningful.
Finally, by multiplying r by itself, one can arrive at the coefficient of determination, which measures the level of variability of a dataset (Triola, 2015). For the r, the coefficient is 0.0144. It means that only 1.44 percent of A can be predicted by B.
Gravetter, F. J., & Wallnau, L. B. (2014). Essentials of statistics for the behavioural sciences (8th ed.). Belmont, CA: Wadsworth Cengage Learning.
Triola, M. F. (2015). Essentials of statistics (5th ed.). New York, NY: Pearson.