Steel Production

Steel Production - Linear Regression Example Problem A...

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Linear Regression Example Problem A steel mill began production in 1986 of a special steel alloy, which has the following production history (production in thousands of tons): Year (x) Output (y) (x 1000 tons) 1986 9.4 1987 10.7 1988 11.0 1990 16.2 1991 22.1 1992 25.8 1993 23.0 1994 24.7 1995 27.3 1996 31.6 (Note that while the time series spans eleven years, only ten years are recorded.) a. By simple regression, determine the equation of the straight line which best fits all the data. b. How “good” is the regression (that is, how strong is the correlation between year index and annual output in kilotons), as measured by the correlation coefficient? c. How much of the variability in the annual steel output cannot be accounted for by regression? d. Calculate a production forecast for 1998. e. The production records for 1989 were lost during a move of the corporate headquarters. Estimate the production for the missing year from the regression line. f. Suppose the peak production (capacity) of the present mill is 50,000 tons (y = 50). When (that is, for what value of x) is capacity expected to be exceeded, if the linear trend of the regression analysis persists? g.
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This note was uploaded on 01/26/2011 for the course OM 210 taught by Professor Singer during the Fall '08 term at George Mason.

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Steel Production - Linear Regression Example Problem A...

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