Consider the following time series data. Week 1 2 3 4 5 6 Value 17 13 17 10 18 15 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE= (b) mean squared error MSE= (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE= % (d) What is the forecast for week 7? Need Help? Read It Watch It Type here to search W L3 72°F B N M

Need a, b and c please

I don’t understand what to do with this table.

Qn4. The stem and leaf plot below gives the truncated average weekly incomes (in THOUSANDS of dollars) of several families. Stem Leaves 1 8 2 1 3 1 40 55 61 5 13499 29 2. Evaluate the following for the actual data value from the stem and leaf plot. (a) What was the highest weekly income range ? (b) What was the lowest weekly income range? (c) How many families are there in the plot? (d) What range does 42 represent?

The number of cans of soft drinks sold in a machine each week is recorded below. Develop forecasts for the period indicated and error calculations. 155, 145, 155, 162, 180, 165, 172, 149, 170, 172 Exponential smoothing.  Use an alpha level of .3   What is the Mean Squared Error (MSE)   What is the Mean Absolute Percentage Error (MAPE)

Please answer part C

A statistical program is recommended. A company that sells musical instruments has been in business for five years. During that time, sales of pianos increased from 12 units in the first year to 76 units in the most recent year. The firm's owner wants to develop a forecast of piano sales for the coming year. The quarterly sales data follow. Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 1 2 3 4 5 4 7 11 12 18 2 4 forecast for quarter 2 forecast for quarter 3 forecast for quarter 4 3 9 10 1 4 5 7 13 5 14 16 22 35 Total Yearly Sales 12 29 35 50 76 (a) Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear trend effects in the data: x₁ = 1 if quarter 1, 0 otherwise; x₂ = 1 if quarter 2, 0 otherwise; and x3 = 1 if quarter 3, 0 otherwise. (Let t = 1 denote the time series value in quarter 1 of year 1; t = 2 denote the time series value in quarter 2 of year 1; ... and t = 20 denote the time series value in quarter 4 of year 5. Round…