Orion is working with a data set that compares the outside temperature, in degrees Celsius, to the number of gallons of ice cream sold per day at a local grocery store. The data has a line of best fit modeled by the function f(x) = 3x + 4 . Orion determines that when the temperature is 25∘C, the store should sell about 79 gallons of ice cream. The correlation coefficient of the data is 0.39.

Explain how accurate Orion expects the prediction to be.

kindly check Explanation.

Step-by-step explanation:

The function f(x) = 3x + 4 is a linear regression model. Orion's prediction was obtained by Substituting 25 for x to obtain the predicted variable

f(25) = 3(25) + 4 = 75 + 4 = 79.

However, with a correlation Coefficient of 0.39, which is a numerical value of range - 1 to +1 and is used to measure the statistical relationship between the dependent variable (number of gallons of ice-cream sold per day) and the independent variable (temperature).

The closer the correlation Coefficient (r) value is to +1 or - 1, the stronger the degree of correlation. Positive r values depicts positive relationship while negative r values depicts negative relationship. The closer the r value is to 0. The weaker the relationship and a r value of means there is no Relationship exists between the two variables.

With a correlation Coefficient of 0.39, we can Infer that that only a moderate positive relationship exists between temperature and gallons of ice cream sold per day.