coefficient shows the relationship strength between two variables.
To analyze the data and in order to test the study hypotheses and discover the significant relationships between dependent and independent variables, descriptive statistics such as frequency, Percentage, mean and inferential statistics such as correlation analysis method by using Pearson's correlation
statistics (were used to describe the extent of correlation and regression).
In defined cell of the correlation matrix, in each cell Pearson's correlation
coefficient, p-value for two tailed test of significance, and the sample size is obtained.
Because the extent of usage may affect electoral success, the relationship between electoral success and the number of Twitter followers, tweets, Facebook posts and "likes" are analyzed using Pearson's correlation
Next, the Pearson's correlation
coefficient was used to determine the relationship between landuse and BI.
In order to measure relationship between constructs of online shopping Pearson's correlation
To test the hypothesis Pearson's correlation
analysis was performed.
was performed between the precipitation, pH, EC and metals concentration in the collected leachates from the fresh and aged spent shale deposit (Tables 3 and 4).
Two types of correlation coefficients are often used in medical research; Pearson's correlation
coefficient is a parametric method that is used to quantify the degree of linearity between two continuous variables and Spearman's correlation coefficient is a non-parametric method to quantify the order of rankings between two continuous variables.
Statistical processing of the findings by a means of Software Package for Social Sciences (SPSS) included the following computations: frequencies of responses, Cronbach's Alpha coefficient, which defines the reliability, and Pearson's correlation
On the other hand, the analysis considering Pearson's correlation
coefficient r and standard error of the estimate SEE of this equation, shown in Table 3, indicates that, for all rolling stands, the predicting performance of the equation virtually had no improvement with the incorporation of the work roll peripherical speed.
coefficients were calculated to determine the correlation of the continuous variables, which included white cell count, protein, and glucose between the two samples of data.