Mrs. matthews has received an invoice from the manufacturer for which she distributes products. the invoice states credit terms of 3/10, net/30. puzzled by this, she calls on you to explain. you indicate that the notation 3/10 means

a) she may take a 30 percent discount if she pays the invoice within three days.
b) she must pay the entire amount in three days.
c) after three days, she must pay the new amount in ten days.
d) her line of credit is equivalent to three-tenths of the dollar value of her business.
e) she may take a 3 percent discount if she pays the invoice within ten days.

In return for their with optimizing his painting project, the castle servant informed poly and digit that he saw someone dressed as the king leaving behind a trail of crumbs as he walked into the jester's room late last night. poly and digit have finally found the crisp-collecting culprit — it turns out the jester's shoe size and hair color match the clues that were found! in gratitude, poly and digit agree to the servant with his current task of replacing all of the tables and chairs in the castle. his goal is to determine which furniture company should produce the new furniture. he receives information from a company that customizes elegant furniture, and he wants to analyze the company's production process in order to calculate some problems about cost and availability. read the following scenario, and assist poly and digit as they the servant with his calculations. the fit for a king furniture company requires 2020 hours of labor to produce a standard table, and a chair requires 1212 hours of labor. the labor available is 565565 hours per week. the company can produce at most 3535 chairs per week.

Joe said “your speech was really great, i loved it.” his criticism lacks which component of effective feedback? a) he did not recognize his ethical obligations b) he did not focus on behavior c) he did not stress the positive d) he did not offer any specifics

True or false: a fitted model with more predictors will necessarily have a lower training set error than a model with fewer predictors.