Multiple Linear Regression - Estimated Regression Equation

X[t] = + 8.89207575757576 -0.0775244755244757Y[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STAT H0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	8.89207575757576	0.368456	24.1333	0	0
Y	-0.0775244755244757	0.050063	-1.5485	0.152536	0.076268

Multiple Linear Regression - Regression Statistics
Multiple R	0.439788816947856
R-squared	0.193414203512395
Adjusted R-squared	0.112755623863634
F-TEST (value)	2.39793713644159
F-TEST (DF numerator)	1
F-TEST (DF denominator)	10
p-value	0.15253637202583
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	0.598670638247972
Sum Squared Residuals	3.58406533100234

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	Interpolation Forecast	Residuals Prediction Error
1	9.486	8.81455128205128	0.671448717948723
2	9.113	8.7370268065268	0.375973193473191
3	9.025	8.65950233100233	0.365497668997668
4	8.476	8.58197785547786	-0.105977855477856
5	7.952	8.50445337995338	-0.552453379953381
6	7.759	8.4269289044289	-0.667928904428905
7	7.835	8.34940442890443	-0.51440442890443
8	7.6	8.27187995337995	-0.671879953379954
9	7.651	8.19435547785548	-0.543355477855478
10	8.319	8.116831002331	0.202168997668999
11	8.812	8.03930652680653	0.772693473193473
12	8.63	7.96178205128205	0.66821794871795