Question

A regression model with quarterly seasonal dummy variables was fit to quarterly sales data (in $10,000) for a small company. The results are shown below. The dummy variables are defined as follows: Q1 = 1 if the time period is Quarter 1, and otherwise. Q2 and Q3 are defined similarly. Abbreviations Used in the Output • "R-Sq" stands for "r squared" • "R-Sq" stands for "adjusted r squared • s stands for "regression standard error," equal to SSE V n-(p+1) The regression equation is Sales = 136 - 31.0 Q1 - 52.0 02 - 51.2 03 Predictor Constant 01 Q2 03 Coef SE Coef 136.167 4.822 -31.000 6.820 -52.000 6.820 -51.167 6.820 T P 28.24 0.000 -4.55 0.000 -7.62 0.000 -7.50 0.000 S = 11.8121 R-Sq = 79.34 R-Sq(adj) = 76.24 What is the forecast (in $10,000) for the second quarter of the next year? Hint: Remember dummy variables can only take on two values: 0 and 1, depending on whether the condition they are measuring is true (1) or false (0). What are the values of the dummy variables Q1, Q2, and Q3 in the second quarter? 105 31 52 136 84

Answer 1

here for given output: for second quarter Q2 =1 while Q1=0 and Q3 =0

therefore forecast for the second quarter of the next year =136.167-52*1 =84