3. What statistical test should be used to predict ice cream sales based on summer's daily temperature? Explain why. 4. Linear regression was conducted to predict individuals' running performance based on their fitness training time. An R-squared of .36 is obtained. What can you conclude from the coefficient of determination? 5. Based on the scatterplot below where the Y axis represents the amount of coffee a person consumes daily, and the X axis represents the person's height. What can you conclude about the correlation coefficient (r) and the relationship between these two variables? 6. What is the difference between simple linear regression and correlation