Data analysis. Statistical Significance of the Parameters

Data analysis. Statistical Significance of the Parameters Statistics Project example
Statistics Project
Finance & Accounting
Pages 12 (3012 words)
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Question 1 Dependent Variable: Y Method: Least Squares Date: 03/15/12 Time: 22:12 Sample: 1 25 Included observations: 25 Coefficient Std. Error t-Statistic Prob.   C 148.2206 221.6269 0.668784 0.5126 X1 -1.287395 0.805735 -1.597788 0.1285 X2 1.809622 0.515248 3.512139 0.0027 X3 0.590396 1.800093 0.327981 0.7469 X4 -21.48169 10.22264 -2.101384 0.0508 X5 5.619403 14.75619 0.380817 0.7081 X6 -14.51467 4.226150 -3.434490 0.0032 X7 29.36026 6.370371 4.608877 0.0003 R-squared 0.961206     Mean dependent var 2109.386 Adjusted R-squared 0.945233     S.D…

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0= -148.2206 ? 1= -1.287395 ? 2= 1.809622 ? 3= 0.590396 ? 4= -21.48169 ? 5= 5.619403 ? 6= -14.51467 ? 7= 29.36026 From the above table, it can be noticed that the constant is -148.22 which means these manhours are available to operate an establishment if there is no factor available. Average daily occupation has the negative relationship with the manhours such that to add 1 extra manhour the average daily occupation will reduce by -1.28. Monthly average number of check-ins has the positive impact on the manhours such that for 1 extra man hour, 1.80 check-in are required. The coefficient for weekly hours of service desk opreration is 0.59 which causes an additional manhour. The common use area has a negative impact on the manhours as every 21.48 square feet will reduce one manhour. ...
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