Question 1 11.0 points possible (graded, results hidden) Linda Howard is the owner of a candy store in Mississippi. She is currently enrolled in SC1x and she is determined to improve the forecast of her best-selling item: the Twisty Candy Roll. Linda's store is located in a popular mall and she has observed seasonality in the demand of Twisty Candy Rolls but no trend. By looking at historical data, she concludes that the demand for this item has seasonality by day of the week, and the seasonality factors that Linda estimated are shared in Table 1. Table 1: Seasonality factors. Day of the week Seasonality factor Monday 0.4 Tuesday 0.6 Wednesday 0.8 Thursday 1 Friday 0.6 Saturday 1.6 Sunday Today is Sunday and Linda has estimated the level to be 100 Twisty Candy Rolls. Assuming that smoothing factors are alpha=0.2 and gamma=0.08, please answer the following question. What would be the forecasted demand for Monday? Round your answer to the nearest integer. Question 2 8.0 points possible (graded, results hidden) Today is Monday, and the actual demand observed today was 70 Twisty Candy Rolls. What would be the forecasted demand for Tuesday? Round your answer to the nearest integer. Linda has been applying another model to forecast demand for her boxes of Assorted Candy Mix. She has been using this model for a while and she wishes to evaluate its performance. In Table 2 you will find the forecasted demand x"(t-1,t) and the actual demand x(t) of two full weeks. Table 2: It Day of the week X(t) *(t-1,t) M 185 75 12 TU 195 85 3 w 82 90 4 TH 187 187 15 |95 87 SA 96 89 17 su 102 90 18 M 105 92 19 TU 98 93 10 W 112 94 11 TH 110 96 12 125 97 13 SA 130 99 14 SU 126 102 What can you conclude from this data? Select all correct statements. Linda is using a Naive model. Linda is using a Cumulative model. Linda is using a Simple Exponential Smoothing model. Linda is using a Holt-Winter model. The demand presents a level. The demand presents a trend. The demand presents seasonality. The model's MAPE is below 30%. The model's MAPE is between 30 and 70%. The model's MAPE is above 70% The model is not biased. The model used is over forecasting. The model used is under forecasting. Question 4 8.0 points possible (graded, results hidden) Linda believes that demand for her Fizzy Ice Creams will be determined by temperature and day of the week. She has built a regression model to predict Fizzy Ice Creams demand using the following two variables: Variable 1: Temperature 1 Variable 2: Weekday or not Demand data for the last 30 days is available in Table 3, as well as average daily temperature (in Farenheit) and day of the week information. Table 3: 3 16 Day Demand Temperature Day of the week 11 188 72 Monday 2 2 87 77 Tuesday 3 74 83 Wednesday 4 88 73 Thursday 15 186 74 Friday 122 183 Saturday 7 185 70 Sunday 18 66 78 Monday 19 56 77 Tuesday 10 52 70 Wednesday 11 66 167 Thursday 12 78 69 Friday 13 114 71 Saturday 14 90 75 Sunday 15 152 69 Monday 16 56 76 Tuesday 17 63 180 Wednesday 18 53 78 Thursday 19 74 67 Friday 20 90 79 Saturday 21 90 184 Sunday 22 64 84 Monday 23 150 184 Tuesday 24 79 69 Wednesday 25 187 79 Thursday 26 64 81 Friday 27 116 78 Saturday 28 87 82 Sunday 29 76 74 Monday 30 88 77 Tuesday What is the adjusted R2 of this model? Write your answer as a decimal number with 4 decimal places (e.g. if your answer is 89.56%, write 0.8956 in the answer box). What is the adjusted R2 of this model? Write your answer as a decimal number with 4 decimal places (e.g. if your answer is 89.56%, write 0.8956 in the answer box). According to this model, what would be the forecast for Fizzy Ice Creams on a Sunday in which average temperature is 89 degrees Fahrenheit? Round your answer to the nearest integer. Question 1 11.0 points possible (graded, results hidden) Linda Howard is the owner of a candy store in Mississippi. She is currently enrolled in SC1x and she is determined to improve the forecast of her best-selling item: the Twisty Candy Roll. Linda's store is located in a popular mall and she has observed seasonality in the demand of Twisty Candy Rolls but no trend. By looking at historical data, she concludes that the demand for this item has seasonality by day of the week, and the seasonality factors that Linda estimated are shared in Table 1. Table 1: Seasonality factors. Day of the week Seasonality factor Monday 0.4 Tuesday 0.6 Wednesday 0.8 Thursday 1 Friday 0.6 Saturday 1.6 Sunday Today is Sunday and Linda has estimated the level to be 100 Twisty Candy Rolls. Assuming that smoothing factors are alpha=0.2 and gamma=0.08, please answer the following question. What would be the forecasted demand for Monday? Round your answer to the nearest integer. Question 2 8.0 points possible (graded, results hidden) Today is Monday, and the actual demand observed today was 70 Twisty Candy Rolls. What would be the forecasted demand for Tuesday? Round your answer to the nearest integer. Linda has been applying another model to forecast demand for her boxes of Assorted Candy Mix. She has been using this model for a while and she wishes to evaluate its performance. In Table 2 you will find the forecasted demand x"(t-1,t) and the actual demand x(t) of two full weeks. Table 2: It Day of the week X(t) *(t-1,t) M 185 75 12 TU 195 85 3 w 82 90 4 TH 187 187 15 |95 87 SA 96 89 17 su 102 90 18 M 105 92 19 TU 98 93 10 W 112 94 11 TH 110 96 12 125 97 13 SA 130 99 14 SU 126 102 What can you conclude from this data? Select all correct statements. Linda is using a Naive model. Linda is using a Cumulative model. Linda is using a Simple Exponential Smoothing model. Linda is using a Holt-Winter model. The demand presents a level. The demand presents a trend. The demand presents seasonality. The model's MAPE is below 30%. The model's MAPE is between 30 and 70%. The model's MAPE is above 70% The model is not biased. The model used is over forecasting. The model used is under forecasting. Question 4 8.0 points possible (graded, results hidden) Linda believes that demand for her Fizzy Ice Creams will be determined by temperature and day of the week. She has built a regression model to predict Fizzy Ice Creams demand using the following two variables: Variable 1: Temperature 1 Variable 2: Weekday or not Demand data for the last 30 days is available in Table 3, as well as average daily temperature (in Farenheit) and day of the week information. Table 3: 3 16 Day Demand Temperature Day of the week 11 188 72 Monday 2 2 87 77 Tuesday 3 74 83 Wednesday 4 88 73 Thursday 15 186 74 Friday 122 183 Saturday 7 185 70 Sunday 18 66 78 Monday 19 56 77 Tuesday 10 52 70 Wednesday 11 66 167 Thursday 12 78 69 Friday 13 114 71 Saturday 14 90 75 Sunday 15 152 69 Monday 16 56 76 Tuesday 17 63 180 Wednesday 18 53 78 Thursday 19 74 67 Friday 20 90 79 Saturday 21 90 184 Sunday 22 64 84 Monday 23 150 184 Tuesday 24 79 69 Wednesday 25 187 79 Thursday 26 64 81 Friday 27 116 78 Saturday 28 87 82 Sunday 29 76 74 Monday 30 88 77 Tuesday What is the adjusted R2 of this model? Write your answer as a decimal number with 4 decimal places (e.g. if your answer is 89.56%, write 0.8956 in the answer box). What is the adjusted R2 of this model? Write your answer as a decimal number with 4 decimal places (e.g. if your answer is 89.56%, write 0.8956 in the answer box). According to this model, what would be the forecast for Fizzy Ice Creams on a Sunday in which average temperature is 89 degrees Fahrenheit? Round your answer to the nearest integer