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- Using a weight of 1/2 for the most recent observation, 1/3 for the second most recent, and 1/6 for third most recent, compute a three-week weighted moving average for the time series. Use rounded for two decimal places values for intermediate calculations. Use minus sign for negative values.Consider the following time series data. a. Show the four-quarter and centered moving average values for this time series (to 3 decimals if necessary). b. Compute seasonal indexes and adjusted seasonal indexes for the four quarters (to 3 decimals).Q.13 Describe models of a time series. CS Scanned with CamScanner
- Q. 27 What are thẹ various methods available for computing seasonal variations in time series ?The following data are annual 15-min peak rainfall intensities I (in./hr) for 9 years of record. Compute and plot the log,,-normal frequency curve and the data. Use the Weibull plotting position formula. Using both the curve and the mathematical equation estimate (a) the 25-yr, 15-min peak rainfall intensity; (b) the return period for an intensity of 7 in./hr; (c) the probability that the annual maximum 15-min rainfall intensity will be between 4 and 6 in./hr.For each of the below ACF plots which are obtained for a time series data of 4 different variables of interest: a) Explain the ACF plot. b) Describe what the raw data is likely to look like over time. c) What kind of variable is this plot likely to characterise (e.g., stock prices, exchange rates, temperature, etc.)?
- Q. 2 Describe the method of Moving averages for estimating the trend in a time seriesThe data in the table above are: A) Cross-sectional B) Quantitative and continuous C) Quantitative and discrete D) Qualitative E) Time-seriesDemand for haircut at PogiPoints Barber Shop has increased steadily for the past few months as seen in the following time series data. Do the necessary computations and choose the best answer that would complete each statement. With alpha = 0.8, the ES forecast for Month 6 would be: * A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts
- Which of the following time series forecasting methods would not be used to forecast seasonal data?Consider the following time series data: Month 1. 3. 5. 7. Value 25 14 19 11 20 24 16 (a) Compute MSE using the most recent value as the forecast for the next period. If required, round your answer to one decimal place. What is the forecast for month 8? If required, round your answer to one decimal place. Do not round intermediate calculation. (b) Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation. What is the forecast for month 8? If required, round your answer to one decimal place. (c) Which method appears to provide the better forecast? Select your answer -The component of a time series attached to long term variations is termed as O a. Secular trend O b. Seasonal trend O c. Cyclic variation O d. Random variation