To find the line of best fit, we can use the equation for a linear regression: y = mx + b, where y is the price, x is the weight in ounces, m is the slope of the line, and b is the y-intercept.
To estimate the price when the weight is 48 ounces, we can plug in x = 48 into the equation: y = mx + b, and solve for y.
The correlation coefficient, denoted by r, is a measure of the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, with -1 indicating a perfect negative correlation, 0 indicating no correlation, and 1 indicating a perfect positive correlation.
In this case, the correlation coefficient means that how strong and direction of the relationship between the price and weight of cereal. A correlation coefficient of 1 means that there is a perfect positive correlation between the two variables, which means that as the weight of the cereal increases, so does the price. A correlation coefficient of -1 means that there is a perfect negative correlation between the two variables, which means that as the weight of the cereal increases, the price decreases. A correlation coefficient of 0 means that there is no correlation between the two variables, which means that there is no relationship between the weight of the cereal and the price.