The following is the list of MAD statistics for each of the models you have estimated from time-series dа ta:

Model MAD

Linear Trend 2.38

Quadratic Trend 3.66

Exponential Trend 4.33

AR (2) 1.97

Based on the MAD criterion, the most appropriate model is:

a) linear trend.

b) quadradic trend.

c) exponential trend.

d) AR (2).

b) quadratic trend.

Step-by-step explanation:

The Mean Absolute Deviation MAD is the value which is calculated by taking sum of deviation of the observations from the mean and divides it by the total number of observations. The quadratic trend is analysis of values over time series, the values will not be constant and will either fall or rise. The quadratic trend gives the lowest value for MAD. The low value for MAD is preferable so the best model which should be used for MAD is quadratic trend.

Step-by-step explanation:

Mean Absolute Deviation is calculated or gotten by firstly by finding the mean of the data set, by finding the addition of the data values, and then by dividing the sum by the number of data values to get the absolute value of the difference between each data value and the mean that is data value - mean. To get the sum of the absolute values of the differences, start by dividing the sum of the absolute values of the differences by the number of data values

In a quadratic trend, the values of a time series sometimes willt rise or it will fall at a rate that is not stable it normally change with time. Thereby, making the line on the trend not to be straight.