[R] Request for functions to calculate correlated factors influencing an outcome.

[Lalitha Viswanathan]

Hi
I have a dataset of the type attached.
Here's my code thus far.
dataset <-data.frame(read.delim("data", sep="\t", header=TRUE));
newData<-subset(dataset, select = c(Price, Reliability, Mileage, Weight,
Disp, HP));
cor(newData, method="pearson");
Results are
                 Price Reliability    Mileage     Weight       Disp
HP
Price        1.0000000          NA -0.6537541  0.7017999  0.4856769
 0.6536433
Reliability         NA           1         NA         NA         NA
NA
Mileage     -0.6537541          NA  1.0000000 -0.8478541 -0.6931928
-0.6667146
Weight       0.7017999          NA -0.8478541  1.0000000  0.8032804
 0.7629322
Disp         0.4856769          NA -0.6931928  0.8032804  1.0000000
 0.8181881
HP           0.6536433          NA -0.6667146  0.7629322  0.8181881
 1.0000000

It appears that Wt and Price, Wt and Disp, Wt and HP, Disp and HP, HP and
Price are strongly correlated.
To find the statistical significance,
I am trying  sample.correln<-cor.test(newData$Disp, newData$HP,
method="kendall", exact=NULL)
Kendall's rank correlation tau

data:  newx$Disp and newx$HP
z = 7.2192, p-value = 5.229e-13
alternative hypothesis: true tau is not equal to 0
sample estimates:
      tau
0.6563871

If I try the same with
sample.correln<-cor.test(newData$Disp, newData$HP, method="pearson",
exact=NULL)
I get Warning message:
In cor.test.default(newx$Disp, newx$HP, method = "spearman", exact = NULL) :
  Cannot compute exact p-value with ties
> sample.correln

Spearman's rank correlation rho

data:  newx$Disp and newx$HP
S = 5716.8, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0
sample estimates:
      rho
0.8411566

I am not sure how to interpret these values.
Basically, I am trying to figure out which combination of factors
influences efficiency.

Thanks
Lalitha
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Price	Country	Reliability	Mileage	Type	Weight	Disp.	HP


8895	USA	4	33	Small	2560	97	113


7402	USA	2	33	Small	2345	114	90


6319	Korea	4	37	Small	1845	81	63


6635	Japan/USA	5	32	Small	2260	91	92


6599	Japan	5	32	Small	2440	113	103


8672	Mexico	4	26	Small	2285	97	82


7399	Japan/USA	5	33	Small	2275	97	90


7254	Korea	1	28	Small	2350	98	74


9599	Japan	5	25	Small	2295	109	90


5866	Japan	NA	34	Small	1900	73	73


8748	Japan/USA	5	29	Small	2390	97	102


6488	Japan	5	35	Small	2075	89	78


9995	Germany	3	26	Small	2330	109	100


11545	USA	1	20	Sporty	3320	305	170


9745	USA	1	27	Sporty	2885	153	100


12164	USA	1	19	Sporty	3310	302	225


11470	USA	3	30	Sporty	2695	133	110


9410	Japan	5	33	Sporty	2170	97	108


13945	Japan	5	27	Sporty	2710	125	140


13249	Japan	3	24	Sporty	2775	146	140


10855	USA	NA	26	Sporty	2840	107	92


13071	Japan	NA	28	Sporty	2485	109	97


18900	Germany	NA	27	Compact	2670	121	108


10565	USA	2	23	Compact	2640	151	110


10320	USA	1	26	Compact	2655	133	95


10945	USA	4	25	Compact	3065	181	141


9483	USA	2	24	Compact	2750	141	98


12145	Japan/USA	5	26	Compact	2920	132	125


12459	Japan/USA	4	24	Compact	2780	133	110


10989	Japan	5	25	Compact	2745	122	102


17879	Japan	4	21	Compact	3110	181	142


11650	Japan	5	21	Compact	2920	146	138


9995	USA	2	23	Compact	2645	151	110


15930	France	NA	24	Compact	2575	116	120


11499	Japan/USA	5	23	Compact	2935	135	130


11588	Japan/USA	5	27	Compact	2920	122	115


18450	Sweden	3	23	Compact	2985	141	114


24760	Japan	5	20	Medium	3265	163	160


13150	USA	3	21	Medium	2880	151	110


12495	USA	2	22	Medium	2975	153	150


16342	USA	3	22	Medium	3450	202	147


15350	USA	2	22	Medium	3145	180	150


13195	USA	3	22	Medium	3190	182	140


14980	USA	1	23	Medium	3610	232	140


9999	Korea	NA	23	Medium	2885	143	110


23300	Japan	5	21	Medium	3480	180	158


17899	Japan	5	22	Medium	3200	180	160


13150	USA	2	21	Medium	2765	151	110


14495	USA	NA	21	Medium	3220	189	135


21498	Japan	3	23	Medium	3480	180	190


16145	USA	3	23	Large	3325	231	165


14525	USA	1	18	Large	3855	305	170


17257	USA	3	20	Large	3850	302	150


13995	USA	NA	18	Van	3195	151	110


15395	USA	3	18	Van	3735	202	150


12267	USA	3	18	Van	3665	182	145


14944	Japan	5	19	Van	3735	181	150


14929	Japan	NA	20	Van	3415	143	107


13949	Japan	NA	20	Van	3185	146	138


14799	Japan	NA	19	Van	3690	146	106