Part b. Calculate a simple linear regression to predict future sales.

1. What is the equation of linear regression?

["y = 78.22 + 15.274 * x + err"

"y = 111.54 + 10.306 * x + err"

"y = 126.74 + 142.854 * x + err"

"y = 126.74 10.306 * x + err"]

2. Using the linear regression, what is the forecast for period 21? ["328", "340", "352", "440"]

3. Using linear regression, what is the Mean Absolute Percent Error (MAPE) of the forecasts for months 1-20? [ Select ] ["7.80%", "2.69%", "9.74%", "5.14%"]

Part c. Calculate the forecast using a moving averages with n = 3

1. What is the forecast for period 21 using the moving averages forecast with N = 3? [ Select ] ["327", "313", "295", "321"]

2. Using the 3-period moving average, what is the Mean Absolute Percent Error (MAPE) of the forecasts for months 1-20? [ Select ] ["Between 16.2% and 17.2%", "Between 9.5% and 10.5%", "Between 12.1% and 13.1%", "Between 14.0% and 15.0%"]

Part d. Why is the linear regression forecast more accurate than the moving average forecast?

"Because the moving average method should never be used as a forecasting method"

"Because the time series has a seasonal pattern"

"Because the linear regression is always a better forecast"

"Because the time series has a positive trend and moving averages forecast is designed for level patterns"]

Month Sales 1 142 2 118 3 144 4 167 5 159 6 156 7 188 8 178 9 202 10 235 11 230 12 217 13 247 14 262 15 261 16 255 17 294 18 306 19 310 20 324

Box Amount 1 455.42 2 630.41 3 593.41 4 493.99 5 459.96 6 591.72 7 693.73 8 642.72 9 575.90 10 406.95 11 494.75 12 567.51 13 494.76 14 416.23 15 575.46 16 502.65 17 502.78 18 411.47 19 414.06 20 537.13 21 529.64 22 628.24 23 486.15 24 538.23 25 679.72 26 450.64 27 588.09 28 438.55 29 430.60 30 458.37 31 623.60 32 487.82 33 418.59 34 650.72 35 540.37 36 487.66