A= Y - B X OR A= - B∑X ∑Y n A= 354.1 × 106 - 810 (437162) 13 A= 354100000 - 354101220 13 A= -1220 = -93.846 OR 13 A -94 ≈ Therefore, the linear regression is Y = 810x 94 – The results showed that the gradient or slope of the linear regression line (where f `(x) = dy = 810 ) dx was equal to the price of the dollar in the world market. That is one dollar in the world market was sold at Tsh. 810/= to meet the costs of the equipment and spare parts required in Bukop factory, and as the price of the dollar in the world market increased in terms of the domestic currency, then the running production costs in the coffee industry would increase at the expense of the price of the coffee paid to the farmers hence to lower the coffee production. This reveals that the higher the price of a dollar, ( foreign currency ) the higher will be the domestic currency required via foreign exchange in the world market to import the equipment
A= Y - B X OR A= ∑Y - B∑X n A= 354.1 × 106 - 810 (437162) 13 A= 354100000 - 354101220 13 A= -1220 = -93.846 OR 13 A ≈ -94 Therefore, the linear regression is Y = 810x – 94 The results showed that the gradient or slope of the linear regression line (where f `(x) = dy = 810 ) dx was equal to the price of the dollar in the world market. That is one dollar in the world market was sold at Tsh. 810/= to meet the costs of the equipment and spare parts required in Bukop factory, and as the price of the dollar in the world market increased in terms of the domestic currency, then the running production costs in the coffee industry would increase at the expense of the price of the coffee paid to the farmers hence to lower the coffee production. This reveals that the higher the price of a dollar, ( foreign currency ) the higher will be the domestic currency required via foreign exchange in the world market to import the equipment
Pascal_final_research.docx