Week-6 (Data-Dive)
- Build at least two pairs of numeric variables
Pair - 1 (ERA vs SO) - We’ll be making a new variable from the pair Earned Run Average vs Strikeouts.
Pairing ERA and Strikeout Rate can help understand a pitcher’s ability to get batters out via strikeouts.
library(ggplot2)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionData_set <- "/Users/ba/Documents/IUPUI/Masters/First Sem/Statistics/Dataset/PitchingPost.csv"
Pitching_Data <- read.csv(Data_set)Pair - 2 (BAOpp vs BB) - We’ll be making a new variable from the pair Opponents Batting Average vs Walks.
Pairing BAOpp with Walk Rate helps assess the impact of a pitcher’s control on their opponents’ batting average.
- Calculate the appropriate correlation coefficient for each of these combinations
Pair - 1
correlation_ERA_SO <- cor(as.numeric(Pitching_Data$ERA), as.numeric(Pitching_Data$IPouts))
print("Correlation between ERA and Strikeouts:")## [1] "Correlation between ERA and Strikeouts:"correlation_ERA_SO## [1] NAis.numeric(Pitching_Data$ERA)## [1] TRUEnumeric_data <- Pitching_Data[, sapply(Pitching_Data, is.numeric)]
cor_data <- data.frame(cor(numeric_data))
cor_data## yearID W L G GS
## yearID 1.000000000 -0.05039952 -0.050935772 -0.022618423 -0.070008561
## W -0.050399522 1.00000000 -0.100676060 0.060533524 0.342589629
## L -0.050935772 -0.10067606 1.000000000 -0.039482862 0.403204575
## G -0.022618423 0.06053352 -0.039482862 1.000000000 -0.263750092
## GS -0.070008561 0.34258963 0.403204575 -0.263750092 1.000000000
## CG -0.068015499 0.22717689 -0.011602536 -0.034010936 0.157894642
## SHO -0.059226332 0.18406634 -0.027130895 -0.023358387 0.114829760
## SV -0.030215996 -0.05279331 -0.065066480 0.267492141 -0.152811548
## IPouts -0.130507979 0.49874427 0.296109478 0.085159721 0.815402701
## H -0.167246573 0.25622704 0.466567960 0.002436191 0.761389283
## ER -0.102501201 0.02716763 0.564306229 -0.031565622 0.592908285
## HR -0.019561900 0.06666310 0.363931196 -0.025688979 0.432270341
## BB -0.116692914 0.16971293 0.288575497 0.049944222 0.544692150
## SO 0.019566275 0.43232013 0.225940111 0.125402244 0.642359403
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB -0.112387813 -0.01005016 0.171820533 0.137328744 0.082859769
## WP -0.024616302 0.04205531 0.104726538 0.052079692 0.145930076
## HBP -0.039069718 0.08316847 0.136819102 0.005027568 0.247214810
## BK -0.008924269 -0.00126845 -0.008769948 0.001788644 -0.001761968
## BFP -0.148611619 0.44707513 0.372495932 0.068379569 0.852168222
## GF -0.048562070 -0.04774859 -0.083572668 0.415395266 -0.327616270
## R -0.112553394 0.02251472 0.590595242 -0.026179491 0.601707599
## SH -0.174366387 0.01862182 0.184129782 0.016375713 0.204848297
## SF -0.061410602 0.04789200 0.114810788 0.032360941 0.164321153
## GIDP -0.093829167 0.19747956 0.118234854 0.038151646 0.345214470
## CG SHO SV IPouts H
## yearID -0.068015499 -0.059226332 -0.0302159957 -0.130507979 -0.167246573
## W 0.227176893 0.184066344 -0.0527933099 0.498744268 0.256227038
## L -0.011602536 -0.027130895 -0.0650664803 0.296109478 0.466567960
## G -0.034010936 -0.023358387 0.2674921413 0.085159721 0.002436191
## GS 0.157894642 0.114829760 -0.1528115479 0.815402701 0.761389283
## CG 1.000000000 0.750369454 -0.0175813520 0.269478509 0.096148421
## SHO 0.750369454 1.000000000 -0.0091197571 0.200508417 0.050727671
## SV -0.017581352 -0.009119757 1.0000000000 -0.012282492 -0.081151957
## IPouts 0.269478509 0.200508417 -0.0122824919 1.000000000 0.743847085
## H 0.096148421 0.050727671 -0.0811519571 0.743847085 1.000000000
## ER -0.004669231 -0.024568202 -0.1070885434 0.454426205 0.770513408
## HR -0.002414783 -0.012185532 -0.0811198544 0.362690431 0.515127592
## BB 0.030533352 0.023387272 -0.0429319705 0.516712460 0.459214675
## SO 0.229741421 0.185312867 0.0343952601 0.825831900 0.552999531
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB -0.027818353 -0.016821003 -0.0003702071 0.125958112 0.179448934
## WP 0.004781032 -0.007429421 -0.0215878488 0.151309199 0.161174525
## HBP 0.010416988 0.013599804 -0.0111141272 0.243247738 0.208487963
## BK -0.007801538 -0.005876852 -0.0116352450 -0.001392093 0.018200448
## BFP 0.226850154 0.164901806 -0.0329272427 0.977359403 0.843613578
## GF -0.044894107 -0.029584766 0.6604916297 -0.127027409 -0.187928284
## R -0.004117169 -0.027877376 -0.1085634207 0.464423061 0.782079256
## SH 0.063091948 0.032537266 -0.0360103313 0.236419304 0.248699100
## SF -0.012544562 -0.022027046 -0.0327901469 0.158130048 0.207994442
## GIDP 0.056821393 0.030802379 -0.0414803010 0.413868651 0.383789974
## ER HR BB SO BAOpp ERA
## yearID -0.102501201 -0.019561900 -0.11669291 0.0195662752 NA NA
## W 0.027167630 0.066663100 0.16971293 0.4323201293 NA NA
## L 0.564306229 0.363931196 0.28857550 0.2259401111 NA NA
## G -0.031565622 -0.025688979 0.04994422 0.1254022444 NA NA
## GS 0.592908285 0.432270341 0.54469215 0.6423594026 NA NA
## CG -0.004669231 -0.002414783 0.03053335 0.2297414213 NA NA
## SHO -0.024568202 -0.012185532 0.02338727 0.1853128671 NA NA
## SV -0.107088543 -0.081119854 -0.04293197 0.0343952601 NA NA
## IPouts 0.454426205 0.362690431 0.51671246 0.8258319002 NA NA
## H 0.770513408 0.515127592 0.45921467 0.5529995314 NA NA
## ER 1.000000000 0.631868353 0.46417322 0.3371917383 NA NA
## HR 0.631868353 1.000000000 0.23917186 0.3032417443 NA NA
## BB 0.464173217 0.239171862 1.00000000 0.4233270529 NA NA
## SO 0.337191738 0.303241744 0.42332705 1.0000000000 NA NA
## BAOpp NA NA NA NA 1 NA
## ERA NA NA NA NA NA 1
## IBB 0.185778658 0.029225019 0.34345578 0.0925356163 NA NA
## WP 0.174337576 0.052112801 0.23152571 0.1568207747 NA NA
## HBP 0.221562513 0.090317648 0.17555315 0.1825334958 NA NA
## BK 0.035743517 0.019514611 0.01997063 -0.0004722306 NA NA
## BFP 0.581741327 0.422261454 0.60862174 0.7974739424 NA NA
## GF -0.186445671 -0.122744162 -0.13522927 -0.0627713418 NA NA
## R 0.972233901 0.621217277 0.47101973 0.3428215165 NA NA
## SH 0.175824774 0.049443090 0.22295322 0.1116538761 NA NA
## SF 0.208955199 0.035150318 0.15595370 0.0613447590 NA NA
## GIDP 0.200107666 0.143960141 0.26779294 0.2300442931 NA NA
## IBB WP HBP BK BFP
## yearID -0.1123878127 -0.024616302 -0.0390697180 -0.0089242694 -0.148611619
## W -0.0100501575 0.042055314 0.0831684728 -0.0012684497 0.447075133
## L 0.1718205327 0.104726538 0.1368191015 -0.0087699483 0.372495932
## G 0.1373287443 0.052079692 0.0050275682 0.0017886442 0.068379569
## GS 0.0828597695 0.145930076 0.2472148099 -0.0017619679 0.852168222
## CG -0.0278183531 0.004781032 0.0104169879 -0.0078015375 0.226850154
## SHO -0.0168210032 -0.007429421 0.0135998041 -0.0058768523 0.164901806
## SV -0.0003702071 -0.021587849 -0.0111141272 -0.0116352450 -0.032927243
## IPouts 0.1259581123 0.151309199 0.2432477375 -0.0013920932 0.977359403
## H 0.1794489336 0.161174525 0.2084879634 0.0182004475 0.843613578
## ER 0.1857786581 0.174337576 0.2215625125 0.0357435169 0.581741327
## HR 0.0292250191 0.052112801 0.0903176485 0.0195146107 0.422261454
## BB 0.3434557811 0.231525713 0.1755531483 0.0199706343 0.608621736
## SO 0.0925356163 0.156820775 0.1825334958 -0.0004722306 0.797473942
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB 1.0000000000 0.078899382 0.0403399451 -0.0036425646 0.176910186
## WP 0.0788993816 1.000000000 0.0503273789 0.0291354703 0.181009330
## HBP 0.0403399451 0.050327379 1.0000000000 -0.0006469978 0.278735367
## BK -0.0036425646 0.029135470 -0.0006469978 1.0000000000 0.006198469
## BFP 0.1769101861 0.181009330 0.2787353672 0.0061984687 1.000000000
## GF 0.0234770814 -0.037414110 -0.0683899987 -0.0172767451 -0.156244821
## R 0.1926961938 0.172811006 0.2232112485 0.0354623104 0.596987773
## SH 0.1765333131 0.042045142 0.1200849472 -0.0184877409 0.264482889
## SF 0.0647043986 0.054699592 0.0721251209 0.0077357587 0.189224314
## GIDP 0.0733023168 0.021582545 0.1490144711 -0.0173513285 0.395149274
## GF R SH SF GIDP
## yearID -0.04856207 -0.112553394 -0.17436639 -0.061410602 -0.09382917
## W -0.04774859 0.022514718 0.01862182 0.047891999 0.19747956
## L -0.08357267 0.590595242 0.18412978 0.114810788 0.11823485
## G 0.41539527 -0.026179491 0.01637571 0.032360941 0.03815165
## GS -0.32761627 0.601707599 0.20484830 0.164321153 0.34521447
## CG -0.04489411 -0.004117169 0.06309195 -0.012544562 0.05682139
## SHO -0.02958477 -0.027877376 0.03253727 -0.022027046 0.03080238
## SV 0.66049163 -0.108563421 -0.03601033 -0.032790147 -0.04148030
## IPouts -0.12702741 0.464423061 0.23641930 0.158130048 0.41386865
## H -0.18792828 0.782079256 0.24869910 0.207994442 0.38378997
## ER -0.18644567 0.972233901 0.17582477 0.208955199 0.20010767
## HR -0.12274416 0.621217277 0.04944309 0.035150318 0.14396014
## BB -0.13522927 0.471019729 0.22295322 0.155953703 0.26779294
## SO -0.06277134 0.342821516 0.11165388 0.061344759 0.23004429
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB 0.02347708 0.192696194 0.17653331 0.064704399 0.07330232
## WP -0.03741411 0.172811006 0.04204514 0.054699592 0.02158254
## HBP -0.06839000 0.223211249 0.12008495 0.072125121 0.14901447
## BK -0.01727675 0.035462310 -0.01848774 0.007735759 -0.01735133
## BFP -0.15624482 0.596987773 0.26448289 0.189224314 0.39514927
## GF 1.00000000 -0.186534359 -0.04737878 -0.034632022 -0.06949020
## R -0.18653436 1.000000000 0.20655696 0.218410368 0.20179584
## SH -0.04737878 0.206556964 1.00000000 0.108214026 0.11045209
## SF -0.03463202 0.218410368 0.10821403 1.000000000 0.07269087
## GIDP -0.06949020 0.201795844 0.11045209 0.072690874 1.00000000typeof(Pitching_Data$ERA)## [1] "double"typeof(Pitching_Data$W)## [1] "integer"x<-as.double(Pitching_Data$W)non_inf_mean <- mean(Pitching_Data$ERA[is.finite(Pitching_Data$ERA)])
non_inf_mean## [1] 5.15709Pitching_Data$ERA[is.infinite(Pitching_Data$ERA)] <- non_inf_meannumeric_data1 <- Pitching_Data[, sapply(Pitching_Data, is.numeric)]
cor_matrix <- cor(numeric_data1)
data.frame(cor_matrix)## yearID W L G GS
## yearID 1.000000000 -0.05039952 -0.050935772 -0.022618423 -0.070008561
## W -0.050399522 1.00000000 -0.100676060 0.060533524 0.342589629
## L -0.050935772 -0.10067606 1.000000000 -0.039482862 0.403204575
## G -0.022618423 0.06053352 -0.039482862 1.000000000 -0.263750092
## GS -0.070008561 0.34258963 0.403204575 -0.263750092 1.000000000
## CG -0.068015499 0.22717689 -0.011602536 -0.034010936 0.157894642
## SHO -0.059226332 0.18406634 -0.027130895 -0.023358387 0.114829760
## SV -0.030215996 -0.05279331 -0.065066480 0.267492141 -0.152811548
## IPouts -0.130507979 0.49874427 0.296109478 0.085159721 0.815402701
## H -0.167246573 0.25622704 0.466567960 0.002436191 0.761389283
## ER -0.102501201 0.02716763 0.564306229 -0.031565622 0.592908285
## HR -0.019561900 0.06666310 0.363931196 -0.025688979 0.432270341
## BB -0.116692914 0.16971293 0.288575497 0.049944222 0.544692150
## SO 0.019566275 0.43232013 0.225940111 0.125402244 0.642359403
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB -0.112387813 -0.01005016 0.171820533 0.137328744 0.082859769
## WP -0.024616302 0.04205531 0.104726538 0.052079692 0.145930076
## HBP -0.039069718 0.08316847 0.136819102 0.005027568 0.247214810
## BK -0.008924269 -0.00126845 -0.008769948 0.001788644 -0.001761968
## BFP -0.148611619 0.44707513 0.372495932 0.068379569 0.852168222
## GF -0.048562070 -0.04774859 -0.083572668 0.415395266 -0.327616270
## R -0.112553394 0.02251472 0.590595242 -0.026179491 0.601707599
## SH -0.174366387 0.01862182 0.184129782 0.016375713 0.204848297
## SF -0.061410602 0.04789200 0.114810788 0.032360941 0.164321153
## GIDP -0.093829167 0.19747956 0.118234854 0.038151646 0.345214470
## CG SHO SV IPouts H
## yearID -0.068015499 -0.059226332 -0.0302159957 -0.130507979 -0.167246573
## W 0.227176893 0.184066344 -0.0527933099 0.498744268 0.256227038
## L -0.011602536 -0.027130895 -0.0650664803 0.296109478 0.466567960
## G -0.034010936 -0.023358387 0.2674921413 0.085159721 0.002436191
## GS 0.157894642 0.114829760 -0.1528115479 0.815402701 0.761389283
## CG 1.000000000 0.750369454 -0.0175813520 0.269478509 0.096148421
## SHO 0.750369454 1.000000000 -0.0091197571 0.200508417 0.050727671
## SV -0.017581352 -0.009119757 1.0000000000 -0.012282492 -0.081151957
## IPouts 0.269478509 0.200508417 -0.0122824919 1.000000000 0.743847085
## H 0.096148421 0.050727671 -0.0811519571 0.743847085 1.000000000
## ER -0.004669231 -0.024568202 -0.1070885434 0.454426205 0.770513408
## HR -0.002414783 -0.012185532 -0.0811198544 0.362690431 0.515127592
## BB 0.030533352 0.023387272 -0.0429319705 0.516712460 0.459214675
## SO 0.229741421 0.185312867 0.0343952601 0.825831900 0.552999531
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB -0.027818353 -0.016821003 -0.0003702071 0.125958112 0.179448934
## WP 0.004781032 -0.007429421 -0.0215878488 0.151309199 0.161174525
## HBP 0.010416988 0.013599804 -0.0111141272 0.243247738 0.208487963
## BK -0.007801538 -0.005876852 -0.0116352450 -0.001392093 0.018200448
## BFP 0.226850154 0.164901806 -0.0329272427 0.977359403 0.843613578
## GF -0.044894107 -0.029584766 0.6604916297 -0.127027409 -0.187928284
## R -0.004117169 -0.027877376 -0.1085634207 0.464423061 0.782079256
## SH 0.063091948 0.032537266 -0.0360103313 0.236419304 0.248699100
## SF -0.012544562 -0.022027046 -0.0327901469 0.158130048 0.207994442
## GIDP 0.056821393 0.030802379 -0.0414803010 0.413868651 0.383789974
## ER HR BB SO BAOpp ERA
## yearID -0.102501201 -0.019561900 -0.11669291 0.0195662752 NA NA
## W 0.027167630 0.066663100 0.16971293 0.4323201293 NA NA
## L 0.564306229 0.363931196 0.28857550 0.2259401111 NA NA
## G -0.031565622 -0.025688979 0.04994422 0.1254022444 NA NA
## GS 0.592908285 0.432270341 0.54469215 0.6423594026 NA NA
## CG -0.004669231 -0.002414783 0.03053335 0.2297414213 NA NA
## SHO -0.024568202 -0.012185532 0.02338727 0.1853128671 NA NA
## SV -0.107088543 -0.081119854 -0.04293197 0.0343952601 NA NA
## IPouts 0.454426205 0.362690431 0.51671246 0.8258319002 NA NA
## H 0.770513408 0.515127592 0.45921467 0.5529995314 NA NA
## ER 1.000000000 0.631868353 0.46417322 0.3371917383 NA NA
## HR 0.631868353 1.000000000 0.23917186 0.3032417443 NA NA
## BB 0.464173217 0.239171862 1.00000000 0.4233270529 NA NA
## SO 0.337191738 0.303241744 0.42332705 1.0000000000 NA NA
## BAOpp NA NA NA NA 1 NA
## ERA NA NA NA NA NA 1
## IBB 0.185778658 0.029225019 0.34345578 0.0925356163 NA NA
## WP 0.174337576 0.052112801 0.23152571 0.1568207747 NA NA
## HBP 0.221562513 0.090317648 0.17555315 0.1825334958 NA NA
## BK 0.035743517 0.019514611 0.01997063 -0.0004722306 NA NA
## BFP 0.581741327 0.422261454 0.60862174 0.7974739424 NA NA
## GF -0.186445671 -0.122744162 -0.13522927 -0.0627713418 NA NA
## R 0.972233901 0.621217277 0.47101973 0.3428215165 NA NA
## SH 0.175824774 0.049443090 0.22295322 0.1116538761 NA NA
## SF 0.208955199 0.035150318 0.15595370 0.0613447590 NA NA
## GIDP 0.200107666 0.143960141 0.26779294 0.2300442931 NA NA
## IBB WP HBP BK BFP
## yearID -0.1123878127 -0.024616302 -0.0390697180 -0.0089242694 -0.148611619
## W -0.0100501575 0.042055314 0.0831684728 -0.0012684497 0.447075133
## L 0.1718205327 0.104726538 0.1368191015 -0.0087699483 0.372495932
## G 0.1373287443 0.052079692 0.0050275682 0.0017886442 0.068379569
## GS 0.0828597695 0.145930076 0.2472148099 -0.0017619679 0.852168222
## CG -0.0278183531 0.004781032 0.0104169879 -0.0078015375 0.226850154
## SHO -0.0168210032 -0.007429421 0.0135998041 -0.0058768523 0.164901806
## SV -0.0003702071 -0.021587849 -0.0111141272 -0.0116352450 -0.032927243
## IPouts 0.1259581123 0.151309199 0.2432477375 -0.0013920932 0.977359403
## H 0.1794489336 0.161174525 0.2084879634 0.0182004475 0.843613578
## ER 0.1857786581 0.174337576 0.2215625125 0.0357435169 0.581741327
## HR 0.0292250191 0.052112801 0.0903176485 0.0195146107 0.422261454
## BB 0.3434557811 0.231525713 0.1755531483 0.0199706343 0.608621736
## SO 0.0925356163 0.156820775 0.1825334958 -0.0004722306 0.797473942
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB 1.0000000000 0.078899382 0.0403399451 -0.0036425646 0.176910186
## WP 0.0788993816 1.000000000 0.0503273789 0.0291354703 0.181009330
## HBP 0.0403399451 0.050327379 1.0000000000 -0.0006469978 0.278735367
## BK -0.0036425646 0.029135470 -0.0006469978 1.0000000000 0.006198469
## BFP 0.1769101861 0.181009330 0.2787353672 0.0061984687 1.000000000
## GF 0.0234770814 -0.037414110 -0.0683899987 -0.0172767451 -0.156244821
## R 0.1926961938 0.172811006 0.2232112485 0.0354623104 0.596987773
## SH 0.1765333131 0.042045142 0.1200849472 -0.0184877409 0.264482889
## SF 0.0647043986 0.054699592 0.0721251209 0.0077357587 0.189224314
## GIDP 0.0733023168 0.021582545 0.1490144711 -0.0173513285 0.395149274
## GF R SH SF GIDP
## yearID -0.04856207 -0.112553394 -0.17436639 -0.061410602 -0.09382917
## W -0.04774859 0.022514718 0.01862182 0.047891999 0.19747956
## L -0.08357267 0.590595242 0.18412978 0.114810788 0.11823485
## G 0.41539527 -0.026179491 0.01637571 0.032360941 0.03815165
## GS -0.32761627 0.601707599 0.20484830 0.164321153 0.34521447
## CG -0.04489411 -0.004117169 0.06309195 -0.012544562 0.05682139
## SHO -0.02958477 -0.027877376 0.03253727 -0.022027046 0.03080238
## SV 0.66049163 -0.108563421 -0.03601033 -0.032790147 -0.04148030
## IPouts -0.12702741 0.464423061 0.23641930 0.158130048 0.41386865
## H -0.18792828 0.782079256 0.24869910 0.207994442 0.38378997
## ER -0.18644567 0.972233901 0.17582477 0.208955199 0.20010767
## HR -0.12274416 0.621217277 0.04944309 0.035150318 0.14396014
## BB -0.13522927 0.471019729 0.22295322 0.155953703 0.26779294
## SO -0.06277134 0.342821516 0.11165388 0.061344759 0.23004429
## BAOpp NA NA NA NA NA
## ERA NA NA NA NA NA
## IBB 0.02347708 0.192696194 0.17653331 0.064704399 0.07330232
## WP -0.03741411 0.172811006 0.04204514 0.054699592 0.02158254
## HBP -0.06839000 0.223211249 0.12008495 0.072125121 0.14901447
## BK -0.01727675 0.035462310 -0.01848774 0.007735759 -0.01735133
## BFP -0.15624482 0.596987773 0.26448289 0.189224314 0.39514927
## GF 1.00000000 -0.186534359 -0.04737878 -0.034632022 -0.06949020
## R -0.18653436 1.000000000 0.20655696 0.218410368 0.20179584
## SH -0.04737878 0.206556964 1.00000000 0.108214026 0.11045209
## SF -0.03463202 0.218410368 0.10821403 1.000000000 0.07269087
## GIDP -0.06949020 0.201795844 0.11045209 0.072690874 1.00000000pair_1 <- Pitching_Data[, c("ERA", "SO")]
ggplot(Pitching_Data, aes(x = ERA, y = SO)) +
geom_point() +
labs(x = "ERA", y = "Strikeouts") +
ggtitle("ERA vs. Strikeouts")## Warning: Removed 22 rows containing missing values (`geom_point()`).
pair_2 <- Pitching_Data[, c("BAOpp", "BB")]
ggplot(Pitching_Data, aes(x = BAOpp, y = BB)) +
geom_point() +
labs(x = "Opponents' Batting Average", y = "Walks") +
ggtitle("Opponents' Batting Average vs. Walks")## Warning: Removed 11 rows containing missing values (`geom_point()`).
correlation_ERA_SO <- cor((numeric_data1$ERA),(numeric_data1$SO))
print("Correlation between ERA and Strikeouts:")## [1] "Correlation between ERA and Strikeouts:"correlation_ERA_SO## [1] NA