To determine whether the relationship between the given X and Y points is nonlinear, we can look at the pattern of the points when plotted on a scatterplot. While I cannot create a scatterplot directly, I can help you analyze the values.
Here are the given points:
- (15, 100)
- (35, 150)
- (100, 350)
- (80, 250)
- (110, 375)
- (60, 225)
- (90, 300)
- (50, 200)
- (25, 125)
- (125, 425)
Step 1: Examine the trend.
To check for linearity, we would typically look to see if the points seem to fall along a straight line. However, with these data points, you can observe that the Y values increase irregularly as X increases.
Step 2: Look for curves:
Given the progression of Y values, particularly noting that the increase in Y isn't consistent (e.g., moving from 100 to 150 increases by 50, but moving from 100 to 350 increases by 250), this suggests a nonlinear trend.
Step 3: Consider mathematical models:
If you were to apply a curve fitting technique (like polynomial regression), you might find that a polynomial or other nonlinear model fits these points better than a simple linear model.
Conclusion:
Based on the progression and distribution of the points, it is likely that the plot of these points would demonstrate a nonlinear relationship. To confirm definitively, you could create a scatterplot and try fitting both linear and nonlinear models to see which provides a better fit.