The statistical correlation between two variables is referred to as their correlation. This value is usually measured on a scale that varies from +1 through 0 to -1 (Ganti, 2020). One of the test statistics that measures the correlation between two variables between two discrete variables is Pearson’s r-value. A positive correlation indicates that the variables move in tandem, while a negative correlation indicates that the two variables move in the opposite direction (Nickolas, 2019). This paper delved into determining Pearson’s r value the population size of U.S. states (2018) and their income in 2018. The data pertaining to the population size of each state was obtained from World Population Review. Based on the data obtained from this site, it was statistically determined if there exists a significant relationship between population size and income in the United States in 2018.
World Population Review is an independent organization. The organization strives to present more recent demographic information on the population of countries and cities. The population size data for each state were obtained from this organization’s website. Based on the data obtained from this website and the dataset from Week 7, the correlation coefficient between population size and income in the United States in 2018 was statistically determined. The results obtained are as shown below:
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| Pearson, r |
-0.0269 |
| N: |
51 |
| T Statistic |
-0.1884 |
| DF |
49 |
| P Value |
0.8514 |
Pearson’s r value was determined and found to be -0.0269. This indicates that there is a negative correlation between population size (2018) and income (2018) in the United States. The negative relationship indicates that as one variable (let us say population size) increases, the other variable (income) decreases (Nickolas, 2019). However, the negative relationship between these two variables is very small. The non-linear relationship between population size and income was determined graphically (Mirindrila, & Balentyne, 2017). The graph obtained is as shown below:
As seen in the graph, the relationship between population size and income is non-linear. This is because the scatter points are randomly distributed (Mirindrila, & Balentyne, 2017). In order to determine the significance of the correlation between population size and income in the United States, it is vital to compare the p-value and our level of significance.
References
Ganti, P. (2020). Correlation coefficient. [Online]. Retrieved April 11, 2020, from https://www.investopedia.com/terms/c/correlationcoefficient.asp
Mirindrila, D., & Balentyne, P. (2017). Scatterplots and correlation. [Online]. Retrieved April 11, 2020, from https://www.westga.edu/academics/research/vrc/assets/docs/scatterplots_and_correlation_notes.pdf
Nickolas, S. (2019). What does it mean if the correlation coefficient is positive, negative, or zero? [Online]. Retrieved April 11, 2020, from https://www.investopedia.com/ask/answers/032515/what-does-it-mean-if-correlation-coefficient-positive-negative-or-zero.asp
