A. Fom the dattached diagram below showing the number of flowers that have bloomed in the garden in the month of March, we can infer that the trend shows a strong positive correlation. If we attempt to draw a straight line to connect some of the points on the plot, we would realized that we're going to be having a line that slopes upward, and also points are either on the line or are at least not far from the line drawn. Having a correlation coefficient or r = 0.98, we can assume that value to be accurate because the trend shows a positive correlation that is closer to a correlation coefficient of 1.
B. A scenario that would show a casual relationship for flowers in the garden is the comparison of the numbers of flowers in the garden and the quantity, in kg of a nutrient-rich fertilizer.
Step-by-step explanation:A. Fom the dattached diagram below showing the number of flowers that have bloomed in the garden in the month of March, we can infer that the trend shows a strong positive correlation. If we attempt to draw a straight line to connect some of the points on the plot, we would realized that we're going to be having a line that slopes upward, and also points are either on the line or are at least not far from the line drawn. Having a correlation coefficient or r = 0.98, we can assume that value to be accurate because the trend shows a positive correlation that is closer to a correlation coefficient of 1.
B. A scenario that would show a casual relationship for flowers in the garden is the comparison of the numbers of flowers in the garden and the quantity, in kg of a nutrient-rich fertilizer.
The first thing we must know in this case is that the distance is equal to the speed for time. We have then: For Chris: d1 = 40 * t For Amy: d2 = 60 * (t-2) The distance between both will be given by the hypotenuse of the rectangle triangle: 300 = root ((40 * t) ^ 2 + (60 * (t-2)) ^ 2) Answer: 300 = root ((40 * t) ^ 2 + (60 * (t-2)) ^ 2) option 3
