A linear regression model is Units = 4,004 – 0.659×Week. For week 46, what is the forecast for the number of units? Round your answer to the nearest whole number.
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A linear regression model is Units = 4,004 – 0.659×Week. For week 46, what is the
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- Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2. 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model you developed in part (b). Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (b) to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, … t = 12 for quarter 4 in year 3. Compute the quarterly forecasts for next year based on the model you developed in part (d). Is the model you developed in part (b) or the model you developed in part (d) more effective? Justify your answer.Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? Is there an indication of a seasonal pattern? b. Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year.A regression line has an intercept value of 174.71 and slope value of 25.22. What is the predicted value (the y-value) in the 100th period (the x-value is 100)? Round to two decimal places.
- In a simple linear regression based on 20 observations, it is found b1 = 3.05 and se(b1) = 1.30. Consider the hypothesis : H0 : β1 = 0 and HA : β1 ≠ 0 . Calculate the value of the test statistic.Calculate the standard deviation of the following returns. Year Return 1 0.01 2 0.27 3 0.02 4 0.02 5 0.22 Enter the answer with 4 decimals, e.g. 0.1234.Use the following information to answer the question. Based on above data, determine the expected return? Select one: a. 12.06% b. 19% c. 17.35% d. 16.72%
- The following 20 observations are for two quantitative variables, x and y. a. Create a scatter chart for these 20 observations. b. Fit a linear trendline to the 20 observations. What can you say about the relationship between the two quantitative variables?Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 8. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 8. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Explain. Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
- Consider the following time series: Construct a time series plot. What type of pattern exists in the data? Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series. What is the forecast for t = 8?Calculate the arithmetic average of the following returns. Year Return1 0.12 20.16 3 0.24 4 0.13 50.02 Enter the answer with 4 decimals, e.g. 0.1234.Consider the following time series data: a. Compute MSE using the most recent value as the forecast for the next period. Whatis the forecast for month 8?b. Compute MSE using the average of all the data available as the forecast for the nextperiod. What is the forecast for month 8?c. Which method appears to provide the better forecast?