Discussion thread six (Correlation and regression)
Reply to: Thomas Woo
Thomas this week’s discussion board was a little challenging but not that bad in that a lot
of the items that we worked with lined up with one another. For example, regarding the
scatterplots this is something that is simple when using this statistical tool that shows the
relationship between two variables. The scatterplots tend to have dots which lets us know the
intersecting lines tend to match up at. We also know that the regression lines or the best fit lines
gets us in the mindset where the two particular sets of information perform in connection with
one another. According to Wali, Tasumi and Moriyama (2020) regression equation determined
by the least-square method, which is a traditional method of statistical analysis; attempts to
describe the relationship by the combination of two linear regression lines. The comment that
you make regarding the straight regression line I agree with in that the positive slope is
connected and are one of the oldest but simplest used in terms of learning and understanding
regression problems. Using the regression lines will allow us to predict the specific target
variable by finding the best linear relationship concerning the dependent and independent
variables. When we look at the Pearson and Spearman correlations that we will use when
measuring the necessary correlation between one another for two unremitting variables. For
question D.6.8.2 (d) I also agree with the selection of using Spearman rho, it makes the
interpreting of the information easier when explaining our findings. “Spearman’s rho is one of
the most popular dependence measures used in practice to describe the association between two
random variables; at least one random variable being discrete, Spearman’s correlations are often
bounded and restricted to a sub-interval” (Mesfiou, Trufin and Zuyderhoff, 2022). These will
allow for making a proper assumption regarding the information that has been established.
References
Mesfioui, M., Trufin, J., & Zuyderhoff, P. (2022). Bounds on Spearman’s rho when at least one random
variable is discrete. European Actuarial Journal, 12(1), 321-348. https://doi.org/10.1007/s13385-02100289-8.
Wali, E., Tasumi, M., & Moriyama, M. (2020). Combination of linear regression lines to understand the
response of sentinel-1 dual polarization SAR data with crop Phenology—Case study in miyazaki,
japan. Remote Sensing (Basel, Switzerland), 12(1), 189. https://doi.org/10.3390/rs12010189.