Following are data on the worldwide shipments of personal computers (in thousands) according to Dataquest. (a) Fit a linear model (T = bo +b¡t) to this data using linear regression. Write the equation for the model, calculate the fitted values and the residuals. Calculate MSE and MAD for this model. (b) Repeat the procedures in (a), but for the quadratic model (T = bo + bịt+ b2t²), using the quadratic regression option in your calculator. %3D (c) Compare MSE for both models and MAD for both models to decide which model fits better. Do not look at R? calculations or other traditional regression diagnostic tools (they are not appropriate for time series - the observations are not independent). Year 1985 Shipments (1000) 14, 705 15,064 16,676 18,061 21,327 23,738 26,966 32,411 38,851 47,894 60,171 71,065 82,400 97,321 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
Following are data on the worldwide shipments of personal computers (in thousands) according to Dataquest. (a) Fit a linear model (T = bo +b¡t) to this data using linear regression. Write the equation for the model, calculate the fitted values and the residuals. Calculate MSE and MAD for this model. (b) Repeat the procedures in (a), but for the quadratic model (T = bo + bịt+ b2t²), using the quadratic regression option in your calculator. %3D (c) Compare MSE for both models and MAD for both models to decide which model fits better. Do not look at R? calculations or other traditional regression diagnostic tools (they are not appropriate for time series - the observations are not independent). Year 1985 Shipments (1000) 14, 705 15,064 16,676 18,061 21,327 23,738 26,966 32,411 38,851 47,894 60,171 71,065 82,400 97,321 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998
MATLAB: An Introduction with Applications
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Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Transcribed Image Text:2. Following are data on the worldwide shipments of personal computers (in thousands)
according to Dataquest.
(a) Fit a linear model (T = bo + bịt) to this data using linear regression. Write the
equation for the model, calculate the fitted values and the residuals. Calculate MSE
and MAD for this model.
%3D
(b) Repeat the procedures in (a), but for the quadratic model (T† = bo + bịt+ bzt²), using
the quadratic regression option in your calculator.
(c) Compare MSE for both models and MAD for both models to decide which model fits
better. Do not look at R? calculations or other traditional regression diagnostic
tools (they are not appropriate for time series - the observations are not independent).
Year
1985
Shipments (1000)
14, 705
15,064
16,676
18,061
21,327
23,738
26,966
32,411
38,851
47,894
60,171
71,065
82,400
97,321
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
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