Concept explainers
Videos
An electrical contractor’s records during the last five weeks indicate the number of job requests:
Predict the number of requests for week 6 using each of these methods:
a. Naive
b. A four-period moving average
c. Exponential smoothing with α = .30; use 20 for week 2
a)
To forecast: The number of requests for week 6 using naïve approach.
Introduction: Forecasting is the planning process that helps to predict the future aspects of the business or operation using present or past data. It uses certain assumptions based the knowledge and experience of the management.
Explanation of Solution
Given information:
Given that an electrical contractor had the following job requests during the last five weeks
Forecast the number of requests for week 6 using the naïve approach as shown below.
Given that the number of job requests for week 5 was 22, the likely job requests for week 6 would also be 22.
b)
To forecast: The number of requests for week 6 using a four-period moving average.
Introduction: Forecasting is the planning process that helps to predict the future aspects of the business or operation using present or past data. It uses certain assumptions based the knowledge and experience of the management.
Explanation of Solution
Given information:
Given that an electrical contractor had the following job requests during the last five weeks
Forecast the number of requests for week6 using a four period moving average as shown below.
Substitute the values to obtain the forecast for week 6 as shown below.
The forecast for week6 would be 20.75
c)
To forecast: The number of requests for week 6 using a exponential smoothing.
Introduction: Forecasting is the planning process that helps to predict the future aspects of the business or operation using present or past data. It uses certain assumptions based the knowledge and experience of the management.
Explanation of Solution
Given information:
Given that an electrical contractor had the following job requests during the last five weeks
Forecast the number of requests for week6 using exponential smoothing as shown below.
Forecast the number of requests for week 6 using an exponential smoothing methodology, given that the forecast for week 2 was 20 and the actual job requests in week 2 was 22, and the exponential smoothing constant
- Given the week 2 forecast was 20, the actual number of jobs in week2 was 22 and the smoothing constant α was 0.3, prepare a forecast for week 3 as shown below.
Therefore, forecasted week3 job requests 20.6.
- Given the week3 forecast was 20.6, the actual number of jobs was 18 and the smoothing constant α was 0.3, prepare a forecast for week4 as shown below.
Therefore, forecasted week4 job requests 19.82.
- Given the week4 forecast was 19.82, the actual number of jobs was 21 and the smoothing constant α was 0.3, prepare a forecast for week5 as shown below.
Therefore, forecasted week5 job requests 20.17.
- Given the week5 forecast was 20.17, the actual number of jobs was 22 and the smoothing constant α was 0.3, prepare a forecast for week 6 as shown below.
Therefore, the forecast for week 6 would be 20.72.
Want to see more full solutions like this?
Chapter 3 Solutions
Operations Management
- The table shows the values found in the error analysis. What method of forecasting would be best to use? What is the forecasted value? MSE forecast for week 13 Time Series 1.08 14.76 3-week MA 3.04 13.67 exp smoothing 11.04 9.5 Group of answer choices A.) Time Series, forecasted value = 14.76 B.) 3-week MA, forecasted value = 13.67 C.) exp smoothing, forecasted value = 9.5 D.) Time Series, forecasted value = 1.08 E.) 3-week MA, forecasted value = 3.04 F.) exp smoothing, forecasted value = 11.04arrow_forwardProfessor Shethinks Shesverybusy needs to allocate time this week for office appointments, so she needs to forecast the number of students who will seek appointments. The professor has gathered the following time series data recently: Period Student Appointments 4 weeks ago 95 3 weeks ago 80 2 weeks ago 65 Last week 50 What is this week's forecast for student appointments using a three-week moving average? а. 52 b. 80 Ос. 65 d. 78 e. 50 O O O Oarrow_forwardWalmart’s Human Resource Planning Forecasting. Walmart’s human resource management forecasts its workforce needs to ensure capacity to address changes in consumer demand. While other forecasting methods and techniques are also used, these three are the most notable at Walmart:arrow_forward
- Problem 3-4 (Static) An electrical contractor's records during the last five weeks indicate the number of job requests: 2 3 22 18 Week: Requests: 1 20 4 21 Click here for the Excel Data File Predict the number of requests for week 6 using each of these methods: a. Naive. 5 22 Answer is complete but not entirely correct. Number of requests 24 X requests b. A four-period moving average. (Round your answer to 2 decimal places.). Answer is complete but not entirely correct. Number of 23.25 c. Exponential smoothing with a = 0.30. Use 20 for week 2 forecast. (Round your intermediate calculations and fina mal nisenelarrow_forwardIn exponential smoothing, if ɑ = 0.3, then the damping factor for use in forecasting should be: * o .70 o .60 o .40 o .50 o .30arrow_forwardAn electronic contractor's records during the last five weeks indicate the number of jobs requests. Week 1 Requests 20 22 18 21 22 Predict the number of requests for week 6 using each of these methods: a. Naïve b. A four period moving average c. Exponential smoothing with a 0.3. Use 20 for week 2 forecast,arrow_forward
- The number of daily calls for the repair of Speedy copy machines has been recorded as follows: a. Prepare three-period moving-average forecasts for the data. What is the error on each day? b. Prepare three-period weighted-moving-average fore-casts using weights of w1= .5, w2= .3, w3= .2. c. Which of the two forecasts is better?arrow_forwardExponential Smoothing, Exponentially Smoothed MAD, and Tracking SignalThe XYZ Company was flooded by a thunderstorm and lost part of its forecasting data.Positions in the table that are marked [a], [b], [c], [d], [e], and [ f ] must be recalculated from the remaining data.arrow_forward4. An electrical contractor's records during the last five weeks indicate the number of job requests: 1 3 20 18 Week Requests 2 22 4 21 5 22 Predict the number of requests for week 6 using each of these methods: a. Naive b. A four-period moving average c. Exponential smoothing with a = 30; use 20 for week 2 forecastarrow_forward
- Figure shows summer air visibility measurements for Denver, Colorado. The acceptable visibility standard is 100, with readings above 100 indicating clean air and good visibility, and readings below 100 indicating temperature inversions caused by forest fires, volcanic eruptions, or collisions with comets.a. Is a trend evident in the data? Which time-series techniques might be appropriate for estimating the average of these data?b. A medical center for asthma and respiratory diseases located in Denver has great demand for its services when air quality is poor. If you were in charge of developing a short-term (say, 3-day) forecast of visibility, which causal factor(s) would you analyze? In other words, which external factors hold the potential to significantly affect visibility in the short term?c. Tourism, an important factor in Denver’s economy, is affected by the city’s image. Air quality, as measured by visibility, affects the city’s image. If you were responsible for development of…arrow_forward10 Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below: Day Bicycle Victims 1 8 2 14 3 8 4 14 5 18 6 15 What is the forecast for day 4 using a 3-period moving average model? (1 mark) (Round to two decimal places). 11 What is the forecast for day 5 using a 3-period moving average model? (Round to two decimal places). 12 What is the forecast for day 6 using a 3-period moving average model? (1 mark) (Round to two decimal places). 13arrow_forward
Practical Management ScienceOperations ManagementISBN:9781337406659Author:WINSTON, Wayne L.Publisher:Cengage,