Final answer:
A scatterplot helps a psychologist visualize data distribution and identify potential relationships between variables, but it does not provide enough evidence to reject the null hypothesis. For statistical significance, the correlation coefficient and the least-squares regression line are calculated.
Step-by-step explanation:
The psychologist has likely created a scatterplot to visualize the distribution of data points. This graphical representation is useful to identify patterns or relationships between two variables, where one variable is designated as the independent variable and the other as the dependent variable. Through inspection of the scatterplot, the psychologist may describe the relationship, if any, between the variables, though a scatterplot alone cannot prove causality.
To determine if there is a statistically significant relationship, the psychologist would calculate the correlation coefficient and the best-fit line using least-squares regression, given by the equation ý = a + bx. If a statistically significant relationship is found, predictions could be made based on the line of best fit. However, the scatterplot itself does not provide sufficient evidence to reject the null hypothesis. For this, further statistical tests would be required.