Given the data below, what is the simple linear regression model that can be used to predict ales in future weeks? Week 1 2 3 4 5 Sales 150 157 162 166 177
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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.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. unitsConsider 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?
- 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?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%1)Find the forecast for 2012 using the time series trend method. Period Demand 2007 200 2008 150 2009 125 2010 100 2011 50 2) Find the forecast for all possible periods N=3, using the data and the moving average method.
- Consider the following time series data: Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8? Compute MSE using the average of all the data available as the forecast for the next period. What is the forecast for month 8? Which method appears to provide the better forecast?Show your work (use of formula, etc.) in solving the problem. Provide your answer/solution in the answer space provided below. Answer the question: Given the following historical returns, calculate the average return and the standard deviation: Year Return 1 14% 2 10% 3 15% 4 11%Boom Nasional Berhad, find the standard deviation. PROBABILITY RETURN 0.35 8% 0.20 3% 0.20 20% 025 15%
- 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.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?Problems 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecasts for the historical data? Explain. Consider the following time series data: Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy: Mean absolute error Mean squared error Mean absolute percentage error What is the forecast for week 7? Refer to the time series data in Problem 1. Using the average of all the historical data as a forecast for the next period, compute the following measures of forecast accuracy: Mean absolute error Mean squared error Mean absolute percentage error What is the forecast for week 7?