An object is thrown from the top of a building. The following data measure the height of the object from the ground for a five second period.
There is a statistically significant correlation between time and height, r = -0.942, p-value = 0.0000454. Should linear regression be used for this data? Why or why not? Answer:
Seconds Height 0.5 112.5 1 110.875 1.5 106.8 2 100.275 2.5 91.3 79.875 3.5 70.083 4 59.83 4.5 30.65Scatterplot Normal Probability Plot 120 150 100 100 Height Height 60 40 50 20 2 4. 50 100 Seconds Sample Percentile Seconds Residual Plot Seconds Line Fit Plot 20 150 10 100 Height Residuals -10 50 -20 30 4 Fi Seconds SecondsO No, there is a curve in the residual plot, normal plot and the scatterplot. 0 Yes, the p-value indicates that there is a significant correlation so we can use linear regression. 0 Yes, there is a nice straight line in the line fit plot. 0 Yes, the normal probability plot has a nice curve to it

Question

An object is thrown from the top of a building. The following data measure the height of the object from the ground for a five second period.

There is a statistically significant correlation between time and height, r = -0.942, p-value = 0.0000454. Should linear regression be used for this data? Why or why not? Answer:

Seconds Height 0.5 112.5 1 110.875 1.5 106.8 2 100.275 2.5 91.3 79.875 3.5 70.083 4 59.83 4.5 30.65Scatterplot Normal Probability Plot 120 150 100 100 Height Height 60 40 50 20 2 4. 50 100 Seconds Sample Percentile Seconds Residual Plot Seconds Line Fit Plot 20 150 10 100 Height Residuals -10 50 -20 30 4 Fi Seconds SecondsO No, there is a curve in the residual plot, normal plot and the scatterplot. 0 Yes, the p-value indicates that there is a significant correlation so we can use linear regression. 0 Yes, there is a nice straight line in the line fit plot. 0 Yes, the normal probability plot has a nice curve to it