Consider the following time series data.Week 1 2 3 4 5 6Value 19 12 1710 17 14Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.(a) mean absolute errorMAE=(b) mean squared errorMSE=(c) mean absolute percentage error (Round your answer to two decimal places.)MAPE=%(d) What is the forecast for week 7?

Week Value 1 19 2 12 3 17 4 10 5 17 6 14

Answered: Consider the following time series…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Consider the following time series data. Week 1 2 3 4 S 9 Value 18 11 14 10 16 13 (a) Construct a time series plot. What type of pattern exists in the data? ◇ The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. The data appear to follow a seasonal pattern. ◇ The data appear to follow a horizontal pattern. (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 18 2 11 3 14 4 10 5 16 6 13 Compute MSE. (Round your answer to two decimal places.) MSE= What is the forecast for week 7?
I need some help with the following problems on excel.
Consider the following time series data. Week 1 3 4 6. Value 19 12 15 10 17 15 Using the naïve 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 (MAPE) Round your answers to two decimal places. МАЕ 3 MSE = МАРЕ - Using the average of all the historical data as a forecast for the next period, compute the same three values. Round your answers to two decimal places. МАЕ 3 MSE = МАРЕ 3 Which method appears to provide the more accurate forecasts for the historical data?
If a forecaster wanted to choose a forecasting model that avoided having a large forecasting error in any given period, which error metric should they use when evaluating their forecasting options? CFE O AFE MAD MAPE O MSE
PART 3 A car mat manufacture been having quality issues with its production. A series of tests were carried out to measure the resulting pH of the most common carpet produced, Type 1, as a good indicator of quality. For the following questions show all calculations and formula used. What is the mean, mode and range of the pH after dyeing? Table – Type 1 pH after addition of dye 5.105 to 5.3 5.305 to 5.5 5.5.05 to 5.7 5.705 to 5.9 5.905 to 6.1 6.105 to 6.3 6.305 to 6.5 No. of samples 1 5 7 8 7 4 1 For pH after addition of dye calculate the standard deviation, showing your calculations in full. Plot the standard deviation graph in Excel showing the distribution. From your calculations and the data Give the minimum and maximum limits the pH may be, given that the distribution is normal. Calculate the probability that a randomly selected carpet sample will have a PH of (i) 6.1 and (ii) 5.4. Further tests were carried on a…
Consider the following time series data. Month 1. 3 4 5 7 Value 20 11 19 11 19 22 15 Round your answers to two decimal places. a. Compute MSE using the most recent value as the forecast for the next period. Mean squared error is What is the forecast for month 8? b. Compute MSE using the average of all data available as the forecast for the next period. Mean squared error is What is the forecast for month 8? c. Which method appears to provide the better forecast? - Select your answer -
I don’t understand what to do with this table.
The figure below illustrates monthly data over 10 years. What method would you expect would perform the best at forecasting the data series in period 121? Explain the (i) strengths of your selected method for this data and the (ii) weaknesses of alternative methods for this data. Consider the concepts of level, seasonality, trend, and noise in your answer.
In Table L-1, the total value of imports of Indonesian goods and services from China for the 2010-2019 period is reported on a quarterly basis. With this data you are asked to analyze it with the Trend model and Seasonal Index. Question: a. Calculate a moving average with the average period length of 4 or MA (4) [why four?] And put the results in a column. Beware of selecting the rows to place the average result. b. Calculate the moving average with the length of the average period is 2 from the data in column MA (4) and the result is given the symbol MA (2x4) and the result is placed in a column. Beware of selecting the rows to place the average result. c. Calculate the ratio to the Moving Average (Y / MA (2x4)) and place it in a new column! d. Calculate a seasonal index and interpret the results! e. Create a Deseasonalized data series and place it in a new column! f. Plot the Dessasonalized data series and read the long-term movement patterns of data! Remember that understanding of…
Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. d. What is the forecast for week 7 (to 2 decimals)?
Define on empirical way and a statistical way to choose the best forecasting model for your time series data. Consider the following situations: 1. The data has no trend or seasonality 2. The data has trend but not seasonality 3. The data presents trend and seasonality but negligible noise 4. The data presents trend, seasonality and significant noise.
c) Following three forecasting techniques were used to predict the value of a time series. These are given in the following table. Forecasting Value F Technique 2 Actual value yt Technique 1 Technique 3 17 21 22 19 27 24 20 24 29 26 25 28 28 32 38 31 31 35 30 39 For each, calculate the mean absolute deviations (MAD) and sum of squares for forecast error (SSFE) to determine which was most accurate.

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