Regression Project

Keller Graduate School of Business Management
Masters of Business Administration

Regression Project
Estimating Stock Prices of Independent E&P Companies

Assignment for Course: HR 533, Applied Managerial Statistics
Submitted to:
Professor Mohamed Nayebpour
Submitted by:
Leah A. O’Daniels

Location of Course: Blended – Houston Campus & On-line
Date of Submission: December 16, 2011

Regression Analysis: StockPrice versus Sales(B)
The regression equation is
StockPrice = 15.64 + 4.441 Sales(B)
S = 11.2028 R-Sq = 33.6% R-Sq(adj) = 31.8%
Analysis of Variance
Source DF SS MS F P
Regression 1 2353.31 2353.31 18.75 0.000
Error 37 4643.62 125.50
Total 38 6996.93

As x increases y increases therefore there is a positive relationship between x and y.
Outlier strong effects the graph of the regression line.

Regression Analysis: StockPrice versus EBITDA(B)
The regression equation is
StockPrice = 13.10 + 16.88 EBITDA(B)
S = 8.79860 R-Sq = 59.1% R-Sq(adj) = 58.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 4132.56 4132.56 53.38 0.000
Error 37 2864.37 77.42
Total 38 6996.93

As x increases y increases, therefore there is a positive relationship between x and y.
Outliers affect the graph of the regression line.

Regression Analysis: StockPrice versus Profit Margin
The regression equation is
StockPrice = 17.09 + 12.97 Profit Margin
S = 13.4077 R-Sq = 4.9% R-Sq(adj) = 2.4%
Analysis of Variance
Source DF SS MS F P
Regression 1 345.58 345.578 1.92 0.174
Error 37 6651.35 179.766
Total 38 6996.93

As x increases y increases between -0. 1 and 0.5 which shows no real pattern to the scatter plot. Therefore this is little or no relationship between x and y.

Regression Analysis: StockPrice versus Earning
The regression equation is
StockPrice = 7.166 +