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Multiple regression analysis

Must see attachment for number 2.

1) What are the components of a time series? What external factors might affect each of the different components?

In number 2, I need assistance step by step details in understanding how to work statistics problems in words of interpretation (that helps explain the results and what it represents) and in EXCEL so that I can understand these types of problems in future problems.

**If charts are use please provide the information if possible on Excel Spreadsheet so I can see how it was done but it canâ??t provide the chart anyway and I will try and figure it out.**

2) A sports enthusiast created an equation to predict Victories (the teamâ??s number of victories in the National Basketball Association regular season play) using predictors FGP (team field goal percentage),
FTP (team free throw percentage), Points = (team average points per game), Fouls (team average number of fouls per game), TrnOvr (team average number of turnovers per game), and Rbnds (team average number of rebounds per game).

The fitted regression was Victories=â?'281 + 523 FGP + 3.12 FTP + 0.781 Points â?' 2.90 Fouls + 1.60 TrnOvr + 0.649 Rbnds (R2 = .802, F = 10.80, SE = 6.87). The strongest predictors were FGP (t = 4.35) and Fouls (t=â?'2.146). The other predictors were only marginally significant and FTP and Rbnds were not significant.

The matrix of correlations is shown below. At the time of this analysis, there were 23 NBA teams.
(a) Do the regression coefficients make sense?
(b) Is the intercept meaningful? Explain.
(c) Is the sample size a problem (using Evansâ??s Rule or Doaneâ??s Rule)?
(c) Why might collinearity account for the lack of significance of some predictors?


Solution Summary

Step by step method for computing regression model is given in the answer.