Answer:
Step-by-step explanation:
The closer the r value is to 1, the stronger the correlation between the numbers. If r is positive, then the slope of the data points tend towards a positive, while if r is negative, then the slope of the data points tend towards a negative. If r = .96, the value is close to 1 and is positive, so it has a strong positive correlation. If r = -.06, the value is far from 1 and is positive, so it has a weak positive correlation. This means that the x and y values for the data do not make sense together. For example, if x was the temperature outside and y was the number of people wearing coats and you observed 20 people outside, a strong correlation coordinate might be (-15, 19). This means that when the temp was -15, 19 people out of 20 will be wearing a coat, which makes sense. If you had that only 2 people wore coats, the data together doesn't make any sense.
