Question

answer the questions below about the scatter plot data.

1. does the scatter plot show positive, negative, or no correlation?
2. sketch the line of best fit. what is a reasonable prediction for toms test grade if he studies for 2 hours?
3. circle the point from the list that would be considered an outlier: (0, 65) (1, 80) (1.5, 55) (3.5, 100)

Explanation:

Step1: Analyze correlation

If points generally rise from left - right, positive correlation; if fall, negative; if no pattern, no correlation. Without the actual scatter - plot, assume a general case. If points show an upward trend, it's positive correlation.

Step2: Sketch line of best fit and predict

To sketch the line of best fit, draw a line that approximates the trend of the data points. To predict Tom's grade when he studies for 2 hours, find the y - value on the line of best fit corresponding to x = 2 on the x - axis (where x is study hours). Without the actual scatter - plot, we can't give a specific value. But if there is a positive correlation, we can estimate based on the trend of the line.

Step3: Identify outlier

An outlier is a point that is far from the other data points. In the set \((0,65),(1,80),(1.5,55),(3.5,100)\), if the general trend is that as x (study hours) increases, y (test grade) increases, the point \((1.5,55)\) might be an outlier as it seems to deviate from the expected upward trend compared to the other points.

Answer:

1. Without the scatter - plot, assume positive correlation if points generally rise from left to right.
2. Without the scatter - plot, can't give a specific prediction. But find the y - value on the line of best fit at x = 2.
3. \((1.5,55)\) (assuming a general upward trend in the data).