Question

Consider the following estimated trend models. Use them to make a forecast for t = 19....

Consider the following estimated trend models. Use them to make a forecast for t = 19.

a. Linear Trend: yˆ = 14.19 + 1.09t (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)

y^= ______________



b. Quadratic Trend: y^ = 18.65 + 0.91t − 0.04t2(Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)

y^: ____________



c. Exponential Trend:  ln(y)^ = 2.1 + 0.08t; se = 0.01 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)

y^: ___________

Homework Answers

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
c. Exponential Trend: ln(y)ˆln(y)^ = 1.8 + 0.05t; se = 0.02 (Round intermediate calculations to at...
c. Exponential Trend: ln(y)ˆln(y)^ = 1.8 + 0.05t; se = 0.02 (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) if t=23 Predicted Y (Y hat)=???
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with...
Consider the following sample regressions for the linear, the quadratic, and the cubic models along with their respective R2 and adjusted R2. Linear Quadratic Cubic Intercept 9.31 9.64 9.70 x 2.56 2.65 1.76 x2 NA −0.30 −0.32 x3 NA NA 0.25 R2 0.782 0.806 0.864 Adjusted R2 0.780 0.803 0.863 a. Predict y for x = 1 and 5 with each of the estimated models. (Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal...
Consider the sample regressions for the linear, the logarithmic, the exponential, and the log-log models. For...
Consider the sample regressions for the linear, the logarithmic, the exponential, and the log-log models. For each of the estimated models, predict y when x equals 70. (Do not round intermediate calculations. Round final answers to 2 decimal places.) Response Variable: y Response Variable: ln(y) Model 1 Model 2 Model 3 Model 4 Intercept 18.36 −6.68 1.47 1.01 x 1.67 NA 0.05 NA ln(x) NA 29.69 NA 0.94 se 23.72 19.55 0.13 0.11
Consider the following population data: 42 48 19 16 28 a. Calculate the range. b. Calculate...
Consider the following population data: 42 48 19 16 28 a. Calculate the range. b. Calculate MAD. (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) c. Calculate the population variance. (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) d. Calculate the population standard deviation. (Round your intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.)
In a simple linear regression based on 28 observations, the following information is provided: yˆ= −6.99...
In a simple linear regression based on 28 observations, the following information is provided: yˆ= −6.99 + 1.15x and se = 2.40. Also, se(y^0) evaluated at x = 28 is 1.46. [You may find it useful to reference the t table.] a. Construct the 95% confidence interval for E(y) if x = 28. (Round intermediate calculations to at least 4 decimal places, "tα/2,df" value to 3 decimal places, and final answers to 2 decimal places.) Confidence interval: b. Construct the...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:      Month Sales (000)Units   Feb. 16   Mar. 19   Apr. 11   May. 22   Jun. 19   Jul. 24   Aug. 21     b. Forecast September sales volume using each of the following:      (Fill in the blanks) (1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.)     Yt __________thousands        (2) A five-month moving average. (Round your answer to 2...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as...
National Scan, Inc., sells radio frequency inventory tags. Monthly sales for a seven-month period were as follows:      Month Sales (000)Units   Feb. 15   Mar. 15   Apr. 10   May. 27   Jun. 15   Jul. 23   Aug. 28     b. Forecast September sales volume using each of the following:      (1) A linear trend equation.(Round your intermediate calculations and final answer to 2 decimal places.)     Yt thousands        (2) A five-month moving average. (Round your answer to 2 decimal places.)        Moving...
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013...
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013 5,441 2010 3,779 2014 5,817 2011 4,504 2015 6,416 (a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.) Linear yt =  t + Exponential yt =  e  t (b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not round the intermediate calculations. Round your final...
Consider a binary response variable y and an explanatory variable x. The following table contains the...
Consider a binary response variable y and an explanatory variable x. The following table contains the parameter estimates of the linear probability model (LPM) and the logit model, with the associated p-values shown in parentheses. Variable LPM Logit Constant −0.69 −6.30 (0.06 ) (0.06 ) x 0.06 0.21 (0.04 ) (0.06 ) a. Test for the significance of the intercept and the slope coefficients at the 5% level in both models. b. What is the predicted probability implied by the...
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013...
JetBlue Airlines Revenue, 2008–2015 (millions) Year Revenue Year Revenue 2008 3,388 2012 4,982 2009 3,286 2013 5,441 2010 3,779 2014 5,817 2011 4,504 2015 6,416 Click here for the Excel Data File (a) Use Excel, MegaStat, or MINITAB to fit both a linear and an exponential trend to the time series. (Round your answers to 2 decimal places.) Linear yt =  t + Exponential yt =  e  t (b) Make annual forecasts for 2016–2018, using the linear and exponential trend models. (Do not...