Final answer:
The Mean Squared Error (MSE) is calculated by finding the mean of the data points, computing the squared errors for each data point, summing them up, and then dividing by the number of points.
Step-by-step explanation:
To compute the Mean Squared Error (MSE) for the given data (11, 13, 12, 14), we first need to calculate the mean (average) of these numbers. Add all the numbers together and then divide by the number of values. The mean of 11, 13, 12, and 14 is (11+13+12+14)/4 = 50/4 = 12.5. Next, we find the squared errors by subtracting the mean from each data point and squaring the result: (11-12.5)², (13-12.5)², (12-12.5)², and (14-12.5)². Calculate each squared error and then find the sum of these squared errors. Finally, divide this sum by the number of data points to get the MSE. Therefore, the MSE is [(11-12.5)² + (13-12.5)² + (12-12.5)² + (14-12.5)²] / 4.