The measures of the central tenancy are a statistical method that finds a way of describing the data using a calculated central value. The three common methods of finding the central tendency are Mode, Mean, and median. On the other hand, the measure of variability is a statistical approach that establishes the dispassion of data points in a dataset. Examples of calculating variability include interquartile range, range, standard deviation, and variance. Both the measures of central tendency and measures of variability analyses the differences of datasets.
Correlation is the degree to which datasets are dependent on each other (Trochim, 2020) . Correlation can be tested statistically using methods such as Independent T-test, and One Way ANOVA (Trochim, 2020) . Independent T-test, test the correlation of the different sets of data using their means (Sirkin, 2006) . For instance, a T-test can be used to investigate the effects of drunk drivers and the number of road accidents. The findings can be reported as follows: When an independent t-statistic was conducted to compare the number of drunk drivers and number of accidents, there was a significant difference in the number of drunk drivers (M= 24 SD= 1.12) and the number of accidents (M= 28 SD= 1.16). t= -7.65 and p= 0.005.” A one ANOVA, on the other hand, tests for the correlation of datasets by the analysis of their variances for more than two groups. Its results are reported in a similar manner (Bewick et al., 2004) . For instance, the result can read: "there are no significant differences in the mean of the three groups using a one way ANOVA (F(2.28)) = 1.286 p= 0.15.”
Delegate your assignment to our experts and they will do the rest.
The current research utilizes a T-test because we are comparing the mean of two datasets. We would require more than two data sets to use ANOVA. As Trochim ( 2020) notes , we would require a binary or continuous variable to use correlation.
References
Bewick, V., Cheek, L., & Ball, J. (2004). Statistics review 9: One-way analysis of variance. Critical Care , 8 (2), 130-136. https://doi.org/10.1186/cc2836
Sirkin, R. (2006). Statistics for the social sciences (p. 276). SAGE.
Trochim, W. (2020). Correlation . Conjointly.com. Retrieved 2 December 2020, from https://conjointly.com/kb/correlation-statistic/ .
Trochim, W. (2020). T-test . Conjointly.com. Retrieved 2 December 2020, from https://conjointly.com/kb/correlation-statistic/.
