Use the tables to create scatter plots and determine which scatter plots shows a linear association
As I do not have access to the specific tables you mentioned, I am not able to create the scatter plots directly. However, I can guide you on how to create the scatter plots and determine a linear association.
To create a scatter plot, you will need the data points from the table, which usually consist of a set of x-values and their corresponding y-values. Assuming you have these data points, you can plot them on a graph, with the x-values on the x-axis and the y-values on the y-axis. Each data point would be represented by a dot on the graph.
Once you have plotted the data points, you can visually analyze the scatter plot to determine if there is a linear association between the variables. A linear association implies that as the x-values increase, the y-values also increase in a consistent manner. Similarly, if the x-values decrease, the y-values also decrease in a consistent manner.
To more accurately determine if the scatter plot shows a linear association, you can use a statistical method such as the correlation coefficient. The correlation coefficient measures the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where a value close to 1 or -1 indicates a strong positive or negative linear association, respectively. A value close to 0 indicates no linear association.
To calculate the correlation coefficient, you can use statistical software or spreadsheet programs such as Microsoft Excel, Google Sheets, or Python libraries like NumPy or Pandas.
Once you have obtained the correlation coefficient value, you can determine if there is a linear association based on whether it is close to 1, -1, or 0. A correlation coefficient close to 1 or -1 indicates a linear association, while a correlation coefficient close to 0 indicates no linear association.
Based on these guidelines, you can examine the scatter plots created from the tables and analyze if they show a linear association.