310projectfinished

310projectfinished - Jeremy K lif BUAD 310 ID: 9128653432...

Info iconThis preview shows pages 1–9. Sign up to view the full content.

View Full Document Right Arrow Icon
Jeremy Klif BUAD 310 ID: 9128653432 STATISTICS PROJECT 1)
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Background image of page 2
a) Commission has no pattern of skeweness. Profit is very roughly normal but left skewed. Area is heavily right skewed because the peaks are on the left and it is unimodal. Outlet is roughly normal and unimodal. Population, on the other hand, is unimodal and it is slightly left skewed. District is multimodal because it has more than 2 peaks but it does not seem to be skewed. b) Summary statistics: Colum n n Mea n Varianc e Std. Dev. Std. Err. Media n Rang e Mi n Ma x Q1 Q3
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
DIST 51 26 221 14.866069 2.081666 26 50 1 51 13 39 Colum n n Mean Variance Std. Dev. Std. Err. Media n Rang e Mi n Max Q1 PROFI T 51 1120.0392 128571.32 358.56842 50.20962 1032 1598 188 1786 878 Summary statistics: Summary statistics: Colum n n Mean Varianc e Std. Dev. Std. Err. Media n Rang e Min Max Q AREA 51 13.064902 49.50234 7.03579 0.9852076 11.2 34.22 6.12 40.34 7.6 Colum n n Mean Varianc e Std. Dev. Std. Err. Media n Rang e Mi n Max Q1 POPN 51 3.7531374 1.180824 9 1.08665 76 0.1521625 3.887 5.447 0.29 7 5.744 3.42 3 Summary statistics: Column n Mean Varianc e Std. Dev. Std. Err. Media n Rang e Mi n Ma x Q1 Q3 OUTLE TS 51 174.0196 933.6596 30.555843 4.278674 174 149 85 234 149 19 Summary statistics:
Background image of page 4
Colum n n Mean Variance Std. Dev. Std. Err. Media n Rang e Mi n Ma x Q1 COMMI S 51 0.627451 0.23843138 0.48829436 0.06837489 1 1 0 1 0 Summary statistics: This data allows us to have an understanding of what the average is for each variable when we evaluate the performance of representatives. c)
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Profit vs Area: slightly strong negatively curved relationship. Profit vs Population: strong linear relationship. Profit vs Outlets: weak positive curved relationship. Profit vs Commission do not seem to have a relationship. d) PROFIT AREA POPN OUTLETS AREA -0.69585794 POPN 0.6221696 -0.8389509 OUTLE TS 0.45451215 -0.6405834 0.7429463 COMMI S 0.26555324 0.13560116 -0.26944116 -0.30914697 There is a strong correlation between area and population with -.839. In this sense, it might cause multicollinearity. On the other hand, commission and outlets or any other variables do not have strong relationiships with any of them. 2) a) Multiple linear regression results: Dependent Variable: PROFIT Independent Variable(s): DIST, AREA, OUTLETS, POPN, COMMIS Parameter estimates:
Background image of page 6
Variabl e Estimate Std. Err. Tstat P- value Intercep t 652.9521 368.1085 1.7738034 0.0829 DIST 2.6920702 2.306625 1.1671035 0.2493 AREA -24.391064 8.349641 -2.921211 0.0054 OUTLE TS 0.9728318 1.5513977 0.627068 0.5338 POPN 87.80185 62.392567 1.4072485 0.1662 COMMI S 345.74167 72.58157 4.763491 <0.0001 Analysis of variance table for multiple regression model: Sourc e D F SS MS F-stat P- value Model 5 4256422 851284.44 17.63594 <0.0001 Error 45 2172144 48269.863 Total 50 6428566 Summary of fit: Root MSE: 219.70404 R-squared: 0.6621 R-squared (adjusted): 0.6246
Background image of page 7

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Residuals stored in new column: Residuals Predicted values stored in new column: Pred. Values b) We can determine if the multiple regression model is useful by looking at the
Background image of page 8
Image of page 9
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 09/11/2011 for the course BUAD 310 taught by Professor Lv during the Spring '07 term at USC.

Page1 / 22

310projectfinished - Jeremy K lif BUAD 310 ID: 9128653432...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online