Compute 3-yearly moving averages of the following data assuming the length Of business cycle as 3 year period and plot the trend va year Annual sales in $ '000 1990 40 1991 42 1590 46 1993 44 1994 49 1995 46 1996 42 1997 44 1998 50
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- What the three trend lines and seasonal variation information shown in Chart and Table1 indicate about historic sales of smart running shoes in Europe and how thisinformation could be used to determine a forecast of sales volumes for our new rangefor the for first 2 quarters of 2022.can you show how to calculate the correlation with the market index with out excelThe following table shows the quarterly sales (RM'000) for Afeef Café for the past 3 years. Quarter Year 1 2 4 2019 11 17 10 18 2020 19 24 17 29 2021 23 38 31 33 Based on the above data, (a) Calculate the trend values using moving average method (correct to 3 decimal places).
- How to test the hypothesis of significant seasonality in the data?Suppose the linear relationship between traffic violations and auto insurance premium has SSR of 2825 and SST of 3150. What percent of the insurance premium is unexplained by traffic violation?show accurate simplistic working out please
- Is age normally distributed“Among those born in 1920, a woman in the lowest income group surviving to 50 could expect to live to age 80. A woman in the highest income group could expect to live to age 84. Use the chart below (and the 1st chart, above) to compute the percentage difference [(final–initial)/initial*100% or change/initial*100%] for Life Expectancy at age 50 for women born in 1920 and 1940 for the top and bottom deciles.The following table shows the daily receipts in millions of dollars of the movie "The Hunger Games" after its opening on 23 March 2012. Days SReceipts 14 33.111 28 14.666 42 5.587 56 2.95 70 1.567 84 0.852 98 0.397 112 0.279 126 0.518 Find the average rate of change of the daily receipts from day 70 to day 126. Preview millions / day
- At the end of Year 5, your consulting firm has been hired by a local service firm to help forecast future uncollectible accounts. You ask the service firm to provide several years of data on the percentage of uncollectible accounts based on the age categories of accounts receivable at the beginning of the year. With these historical percentages, you estimate a trend line (dashed line) to predict the percentage of uncollectible accounts for Year 6, the upcoming year. Graphs were provided to management from your analysis of each of the three age categories, as well as balances of accounts receivable by age category at the end of Year 5 as follows: Percentage of Uncollectible Accounts: 1-30 Days Past Due 8% 6% 4% 2% 0% 4% Year 1 Not Yet Past Due 2 3% 3 5% 5 6% 6 $140,000 $120,000 $100,000 $80,000 $60,000 $40,000 $20,000 8 $0 18% 16% 14% 12% 10% 16% 14% Year 1 2 3 $128,000 14% Not Yet Past Due Accounts Receivable by Age: End of Year 5 $84,000 15% 1-30 Days Past Due 6 46% 44% 42% 40% 38%…After the final adjusted seasonal indexes are determined, the original data can be O Discarded Detected Deseasonalized DeregulatedThe following is the production data for fried indomie (million pcs) in 2011 - 2020 consecutively as follows: 3, 8, 14, 13, 15, 16, 12, 17, 18, 17. Determine the value of the production trend using Moving Average Method!