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QMB TEST 3 CHEATSHEET - FALL EXAM 3 Listed below is...

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FALL EXAM 3 Listed below is computer output from a program somewhat like PhStat for a study of home prices over a 4-month period of time in one section of the Dallas-Ft. Worth metropolitan area. The data was collected several years ago during a generally weakening economy, so we expect to see falling prices over time. In the analysis, home size is accounted for by using price per square foot ( PriPrSqFt ) as the dependent variable. The independent variable is Mnth , which has a value of 3, 4, 5 or 6 to designate March through June. USE THIS INFORMATION TO ANSWER THE QUESTIONS ON PAGE THREE. Simple Regression Analysis ══════════════════════════════════════════════════════════════════════════════ Linear model: PriPrSqFt = 63.8534 - 1.60673*Mnth Table of Estimates ══════════════════════════════════════════════════════════════════════════════ Standard t P Estimate Error Value Value ══════════════════════════════════════════════════════════════════════════════ Intercept 63.8534 1.02858 62.08 0.0000 Slope -1.60673(b 1 ) 0.22664(SE b1 ) ttttt 0.0000 ══════════════════════════════════════════════════════════════════════════════ R-squared = RSQRSQ Correlation coeff. = rrrrrr Standard error of estimation = 4.05338 Sample size (n) = 243 ══════════════════════════════════════════════════════════════════════════════ Analysis of Variance ══════════════════════════════════════════════════════════════════════════════ Sum of P Source Squares D.F. Mean Square F-Ratio Value ══════════════════════════════════════════════════════════════════════════════ Regression(SSRegres) 825.748 1 825.748 50.26 0.0000 Residual 3959.6 241 16.4299 ══════════════════════════════════════════════════════════════════════════════ Total(SSTOTAL) 4785.35 242 Table of Predicted Values
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