Week 3: Data Visualization

Hello everyone, welcome to my week 3 blog. This week’s goal is to visualize my dataset using scatter plots and linear regression summaries.

From the scatter plots and linear regression summaries, we can draw some basic predictions. For scatter plots that do not show a linear pattern simply means that the Y-axis has no relationship with X-axis. Each Time Series Plot identifies trends, patterns, or outliers in the dataset. In all the scatter plots: Temperature vs. pH, Temperature vs. TDS, and pH vs. TDS, the graph does not seem to show a linear relationship. Therefore, the variables do not have a direct linear relationship between each other. However, in the coefficients for the Temperature vs. pH graph, we observe that for each degree increase in temperature, the pH is expected to increase by about 3.0647, assuming all other factors remain constant. A similar relationship is observed from the coefficient value for pH vs. TDS. Next week, I will choose to focus more on predicting the R-squared value and intend to begin analyzing the data using the Model of Goodness data analysis.