$1.$ Please respond to the weekly forum $2$ provided in Week $2.$

$2.$ Forecast demands using weighted moving average. Please apply weights of $0\mathrm{.}3$ for the most

recent period, then $0\mathrm{.}4,$ then $0\mathrm{.}3$

$16212314418522625728$

$3.$ Given the following data: a$)$

Period

Demand

Forecast

Prepare a forecast using smoothing constant a $=0\mathrm{.}40.$

b$)$

Subjective estimate $($for this example, use $60).$

First actual value $($na$$ve approach$).$

Period

Actual

Forecast

$163252356462$

$4.$ Given the following data:

c$)$ d$)$

What are the exponential smoothing forecasts for periods $2-5$ using a $=0\mathrm{.}7?$

Use na$$ve approach for $1$st week

Week

Demands

$1830$

$2765$

$3630$

$4640$

$5$

$1$

Predict quarterly demand for a certain loveseat. The series has both trend and seasonality and

the Quarterly relatives are: Q$1=1\mathrm{.}20,$ Q$2=1\mathrm{.}10,$ Q$3=0\mathrm{.}75,$ Q$4=0\mathrm{.}95.$ If the trend equation equals

to yt$=124+7\mathrm{.}5$t $($t $=$ quarter $15),$ Predict demand for quarter $2($where t $15=$ quarter $2).$

$5.$

$6.$

Given the following data, compute MAD, MSE, and MAPE for the following data. Then, please

compute the standard deviation of forecast error using the first eight months.

Months

Demand

Forecast

$7.$

$12102240323042405280622272208250$

$215$

$235$

$200$

$305$

$310$

$222$

$235$

$225$

$245$

$265$

$250$

$220$

$273$

n$/$a $255203325320$

Below are a pharmacy$$s actual sales and forecasted demand for a certain prescription drug for $5$

months. How accurate is their forecast? Calculate MAD and MSE and create a control chart.

Months

Actual sales

Forecasted demand

$12345$

$8.$ Freight car loadings during a $14-$week period at a port are:

$1232822509327010426211532012635213737514$

$385$

$420$

$465$

$485$

$498$

$520$

$555$

Week

Number

Week

Number

a$)$ b$)$

Compute a linear trend line for freight car loadings using of Excel$$s Trendline, with display

Equation on chart option.

Use the trend equation to predict loadings for weeks $15$ and $16.$

$2$

Given the following data, determine the total annual cost of making with each of process A

and B and of buying. Estimated demand is $8,500$ units a year. The operations manager has said

that it would be possible to achieve a $12$ percent reduction in the fixed cost of Process B and a

$12$ percent reduction in B$$s variable cost per unit. Would that be enough to change your answer

if the estimated annual cost to achieve those savings was $$5,000?$

$9.$

Variable cost per unit Annual fixed cost Transportation cost per unit

$10.$

$$49$ $$42000$

$$51$ $$50$ $$34000$

$$2$

Make

Process A

Process B

Process C

A manager must decide on delivery alternatives. There are two carriers, A and B$.$ Both offer a

two$-$day rate. In addition, A offers a three$-$day rate and a nine$-$day rate, and B offers a four$-$day

rate and a seven$-$day rate. Three hundred boxes are to be delivered and the freight cost for the

whole lot for each option is given below. Annual holding cost is $20$ percent of unit cost, and

each box has a cost of $$120.$ Assume $365$ days per year. Which delivery alternative would you

recommend?

Cashier A

Cashier B

Options

Freight Cost

Options

Freight Cost

$2$ days $3$ days $9$ days

$$580$

$$520$

$$450$

$2$ days $$5104$ days $$4407$ days $$400$

$11.$ Analyze the following data to determine the total annual cost of making or buying a part.

Expected annual quantity Variable cost per unit Annual fixed costs

Freight Cost

Make

Buy

$20,000$ units $20,000$ units $$5\mathrm{.}00$ $$6\mathrm{.}00$

$$30,000$

$12.$ Multiple choice question: The use of simpler linear regression analysis assumes that:

a$)$ b$)$ c$)$

Variations around the line are non$-$random.

A straight line will be determined that maximizes the sum of deviations of the data points.

Predictions are to be made only within the range of observed values of the predictor

variable.

$3$

d$)$ e$)$

$13.$ Please answer the following True or False questions.

Deviations around the line are not normally distributed.

Predictions can be made outside the range of observed values of the predictor variable.

a$)$ When error values fall outside the limits of a control chart, this signals a need for corrective action. $($True$/$False$)$

b$)$ When all errors plotted on a control chart are either all positive or all negative, this shows that the forecasting technique is performing adequately. $($True$/$False$)$

c$)$ A random pattern of errors within the limits of a control chart signals a need for corrective action. $($True$/$False$)$