Multiple Linear Regression - Estimated Regression Equation
FINAL[t] = -4.33610240124024 + 0.355938218661821EXAM1[t] + 0.542518757618704EXAM2[t] + 1.16744421628222EXAM3[t] + e[t]


Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STAT
H0: parameter = 0
2-tail p-value1-tail p-value
(Intercept)-4.336102401240243.764226-1.15190.2622980.131149
EXAM10.3559382186618210.1213892.93220.0079610.003981
EXAM20.5425187576187040.1008495.37952.5e-051.2e-05
EXAM31.167444216282220.10301411.332900


Multiple Linear Regression - Regression Statistics
Multiple R0.994817359591619
R-squared0.98966157894484
Adjusted R-squared0.988184661651246
F-TEST (value)670.085984663602
F-TEST (DF numerator)3
F-TEST (DF denominator)21
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.61356514949275
Sum Squared Residuals143.445178603504


Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolation
Forecast
Residuals
Prediction Error
1152152.607204391736-0.607204391735592
2185185.080114719002-0.0801147190015528
3180181.781585468364-1.78158546836372
4196199.74522646515-3.7452264651496
5142139.1747207036632.82527929633742
6101103.693917933819-2.69391793381877
7149150.26322740394-1.26322740394047
8115112.8206972794462.17930272055401
9175174.5594839396160.440516060384367
10164164.494420939188-0.494420939188291
11141143.423375508337-2.42337550833677
12141142.234164155187-1.2341641551873
13184186.542857589768-2.54285758976804
14152152.407945271142-0.40794527114202
15148151.244091081266-3.24409108126581
16192189.1249661254672.87503387453308
17147143.5021921829763.49780781702442
18183181.8938936102971.10610638970288
19177177.298389142192-0.298389142191725
20159158.3493401904650.650659809534807
21177176.5774241496370.422575850362542
22175174.6636577775280.336342222472297
23175167.6888939207237.31110607927704
24149150.632798455448-1.63279845544823
25192191.1954115956450.80458840435502