CUNY SPS R-WORKSHOP
Final Assignment
Tage N Singh
This Project use A Consolidate Dataset From 1969 to 1989 and is accessed from github.
The Question ? ?
– Is THERE CORRELATION ACROSS REGIONS/STATES (AND DC) IN THE US AMONG THE FOLLOWING : :
– US BIRTH RATES
– MEDIAN HOUSEHOLD INCOME
– PER CAPITA HOUSEHOLD INCOME
– US GROSS DEOMESTIC PRODUCT (GDP)
– FOR THE DECADES ENDING 1969, 1979,1989
– ( CURRENT DOLLARS)
- (:
library(datasets)
library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.0.3library(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, unionlibrary("tidyverse")## Warning: package 'tidyverse' was built under R version 4.0.3## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --## v tibble 3.0.6 v purrr 0.3.4
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## Warning: package 'tibble' was built under R version 4.0.3## Warning: package 'readr' was built under R version 4.0.3## Warning: package 'forcats' was built under R version 4.0.3## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()popstatsURL <- ("https://raw.githubusercontent.com/tagensingh/SPS-WRKSHP-R-FINAL-PROJECT/master/1-SPS-Project-Consolidate-Data.csv")
popstatsURL <- ("1-SPS-Project-Consolidate-Data.csv")
popstats1 <- read.table(file =popstatsURL, header = TRUE , sep = ",")
summary(popstats1)## Region_Code Region State State.Name
## Min. : 1.000 Length:51 Length:51 Length:51
## 1st Qu.: 3.000 Class :character Class :character Class :character
## Median : 5.000 Mode :character Mode :character Mode :character
## Mean : 5.667
## 3rd Qu.: 8.000
## Max. :11.000
## X1969.Births X1979.Births X1989.Births X1969.GDP.C.DLS
## Min. : 5874 Min. : 7292 Min. : 6768 Min. : 1798
## 1st Qu.: 19306 1st Qu.: 19883 1st Qu.: 20201 1st Qu.: 4102
## Median : 47896 Median : 47389 Median : 50381 Median : 9622
## Mean : 70569 Mean : 68622 Mean : 76741 Mean : 18881
## 3rd Qu.: 86444 3rd Qu.: 78964 3rd Qu.: 85797 3rd Qu.: 20260
## Max. :352858 Max. :379212 Max. :533429 Max. :107031
## X1979.GDP.C.DLS X1989.GDP.C.DLS X1969.Med.HH.Inc X1979.Med.HH.Inc
## Min. : 4399 Min. : 10730 Min. : 5221 Min. :12096
## 1st Qu.: 12505 1st Qu.: 27255 1st Qu.: 7132 1st Qu.:14770
## Median : 33496 Median : 65526 Median : 8199 Median :16647
## Mean : 48812 Mean :105217 Mean : 8163 Mean :16631
## 3rd Qu.: 52526 3rd Qu.:120929 3rd Qu.: 9196 3rd Qu.:17804
## Max. :293491 Max. :722979 Max. :11817 Max. :25414
## X1989.Med.HH.Inc X1969.HH.Inc.Per.C.DLS X1979.HH.Inc.Per.C.DLS
## Min. :20136 Min. :13935 Min. :19675
## 1st Qu.:25637 1st Qu.:18778 1st Qu.:23826
## Median :28706 Median :21370 Median :27088
## Mean :29135 Mean :21344 Mean :26924
## 3rd Qu.:31682 3rd Qu.:23969 3rd Qu.:28935
## Max. :41721 Max. :28124 Max. :38693
## X1989.HH.Inc.Per.C.DLS
## Min. :20576
## 1st Qu.:25369
## Median :28617
## Mean :29348
## 3rd Qu.:32433
## Max. :43057– Fixing The Headers
popstats2 <- popstats1
names(popstats2)[1] <- "Region_Code"
names(popstats2)[2] <- "Region_Name"
names(popstats2)[3] <- "State_Code"
names(popstats2)[4] <- "State_Name"
names(popstats2)[5] <- "Births_1969"
names(popstats2)[6] <- "Births_1979"
names(popstats2)[7] <- "Births_1989"
names(popstats2)[8] <- "GDP_1969"
names(popstats2)[9] <- "GDP_1979"
names(popstats2)[10] <- "GDP_1989"
names(popstats2)[11] <- "Median_HH_Inc_1969"
names(popstats2)[12] <- "Median_HH_Inc_1979"
names(popstats2)[13] <- "Median_HH_Inc_19689"
names(popstats2)[14] <- "Per_Capita_HH_Inc_1969"
names(popstats2)[15] <- "Per_Capita_HH_Inc_1979"
names(popstats2)[16] <- "Per_Capita_HH_Inc_1989"
head(popstats2, 6)## Region_Code Region_Name State_Code State_Name Births_1969 Births_1979
## 1 11 West CA California 352858 379212
## 2 11 West HI Hawaii 15750 17568
## 3 11 West NV Nevada 8902 12293
## 4 10 Southeast AL Alabama 64068 61688
## 5 10 Southeast FL Florida 106926 120774
## 6 10 Southeast GA Georgia 91622 89582
## Births_1989 GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 1 533429 106629 293491 722979 9302 18243
## 2 19051 4262 11869 29427 10675 20473
## 3 17894 2947 10295 27847 9505 18211
## 4 59917 11866 33712 68394 6419 13669
## 5 183968 27428 86263 241633 7168 14675
## 6 107023 18082 51550 133794 7346 15033
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 1 35798 26162 31488
## 2 38829 24418 29381
## 3 31011 25728 32088
## 4 23597 16773 22374
## 5 27483 22137 27597
## 6 29021 19111 24302
## Per_Capita_HH_Inc_1989
## 1 34995
## 2 33633
## 3 32447
## 4 24496
## 5 31346
## 6 29071####Computing the correlation By State
popstats31 <- subset(popstats2, Region_Code == "1",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats32 <- subset(popstats2, Region_Code == "2",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats33 <- subset(popstats2, Region_Code == "3",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats34 <- subset(popstats2, Region_Code == "4",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats35 <- subset(popstats2, Region_Code == "5",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats36 <- subset(popstats2, Region_Code == "6",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats37 <- subset(popstats2, Region_Code == "7",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats38 <- subset(popstats2, Region_Code == "8",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats39 <- subset(popstats2, Region_Code == "9",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats40 <- subset(popstats2, Region_Code == "10",select=Region_Name:Per_Capita_HH_Inc_1989)
popstats41 <- subset(popstats2, Region_Code == "11",select=Region_Name:Per_Capita_HH_Inc_1989)
head(popstats31, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 51 Far West AK Alaska 6824 9005 11105
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 51 2074 10891 23453 11817 25414
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 51 41408 26966 38693
## Per_Capita_HH_Inc_1989
## 51 37557head(popstats32, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 45 Great Lakes IL Illinois 193136 181153 181679
## 46 Great Lakes IN Indiana 94562 87380 81635
## 47 Great Lakes MI Michigan 163940 143237 137965
## 48 Great Lakes MN Minnesota 65958 65744 66409
## 49 Great Lakes OH Ohio 189544 167117 161647
## 50 Great Lakes WI Wisconsin 74044 72839 70385
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 45 60840 139253 266608 9706 19321
## 46 24212 57918 107199 8921 17582
## 47 47895 105413 190626 9997 19223
## 48 17681 46861 98313 8753 17761
## 49 52817 117117 217817 9279 17754
## 50 19521 50101 95217 8997 17680
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 45 32252 25301 30619
## 46 28797 22224 27111
## 47 31020 24302 29184
## 48 30909 21993 28284
## 49 28706 23158 27654
## 50 29442 21949 27494
## Per_Capita_HH_Inc_1989
## 45 32419
## 46 28043
## 47 30186
## 48 30687
## 49 28708
## 50 28314head(popstats33, 6)## Region_Name State_Code State_Name Births_1969 Births_1979
## 37 Midsouth DC District of Columbia 27780 20232
## 38 Midsouth DE Delaware 10116 9184
## 39 Midsouth KY Kentucky 58276 60030
## 40 Midsouth MD Maryland 60326 50980
## 41 Midsouth NC North Carolina 93956 84249
## 42 Midsouth TN Tennessee 73248 72148
## Births_1989 GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 37 21351 8096 18417 37469 8283 16211
## 38 10959 3069 7304 18900 9309 17846
## 39 50381 13206 35838 65526 6537 13965
## 40 68083 17385 43628 107444 10101 20281
## 41 97868 20882 54515 133866 7025 14481
## 42 75595 15167 42194 91579 6631 14142
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 37 30727 27813 34012
## 38 34875 23636 28276
## 39 22534 17555 22692
## 40 39386 25424 31480
## 41 26647 17910 23281
## 42 24807 17837 23585
## Per_Capita_HH_Inc_1989
## 37 40268
## 38 33812
## 39 23786
## 40 37813
## 41 27480
## 42 26136head(popstats34, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 31 Midwest IA Iowa 47896 47321 38361
## 32 Midwest KS Kansas 35456 37419 37574
## 33 Midwest MO Missouri 81266 78562 78331
## 34 Midwest ND North Dakota 11276 12752 11441
## 35 Midwest NE Nebraska 24806 26566 24266
## 36 Midwest SD South Dakota 11276 12858 11253
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 31 12332 33496 52907 7880 16799
## 32 9166 26300 48814 7578 16362
## 33 21095 50601 101412 7672 15581
## 34 2178 7218 10730 6909 15293
## 35 6537 17423 31332 7426 15925
## 36 2273 6716 11790 6450 13156
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 31 26229 20878 27088
## 32 27291 21204 27901
## 33 26362 21370 26257
## 34 23213 17874 24359
## 35 26016 20248 26329
## 36 22503 17280 21626
## Per_Capita_HH_Inc_1989
## 31 26492
## 32 28365
## 33 27702
## 34 23568
## 35 26556
## 36 22737head(popstats35, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 24 Mountain West AZ Arizona 34064 46714 65655
## 25 Mountain West CO Colorado 40100 47741 53518
## 26 Mountain West ID Idaho 13072 19533 15563
## 27 Mountain West MT Montana 11620 13804 11393
## 28 Mountain West NM New Mexico 21316 24768 26686
## 29 Mountain West UT Utah 24810 42095 37021
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 24 7563 27495 67896 8199 16448
## 25 9480 33785 71179 8423 18056
## 26 2750 9286 16909 7482 15285
## 27 2761 8173 12630 7436 15420
## 28 4091 13141 24927 7096 14654
## 29 4036 13709 28668 8482 17671
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 24 27540 21262 26728
## 25 30140 22485 30360
## 26 25257 19140 23717
## 27 22988 19517 25012
## 28 24087 17642 23228
## 29 29470 19524 23934
## Per_Capita_HH_Inc_1989
## 24 28708
## 25 31609
## 26 24434
## 27 23914
## 28 23984
## 29 23522head(popstats36, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 18 New England CT Connecticut 49184 38445 48152
## 19 New England MA Massachusetts 94852 72283 89958
## 20 New England ME Maine 17296 15810 16520
## 21 New England NH New Hampshire 12288 12819 17053
## 22 New England RI Rhode Island 15854 12251 14689
## 23 New England VT Vermont 7778 7292 7871
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 18 15628 36855 95831 10877 20077
## 19 27476 62965 158200 9563 17575
## 20 3695 9335 22670 7315 13816
## 21 2817 8351 23777 8652 17013
## 22 4113 8845 21059 8617 16097
## 23 1798 4399 11120 7961 14790
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 18 41721 28124 32308
## 19 36952 24671 28311
## 20 27854 18445 21895
## 21 36329 21609 26443
## 22 32181 22594 26181
## 23 29792 20067 23452
## Per_Capita_HH_Inc_1989
## 18 43057
## 19 36734
## 20 27633
## 21 34036
## 22 31950
## 23 28849head(popstats37, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 16 North West OR Oregon 34486 42870 41345
## 17 North West WA Washington 59238 63819 71396
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 16 9353 28372 52610 8296 16780
## 17 18091 48713 108064 9125 18367
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 16 27250 22789 28686
## 17 31183 24302 30645
## Per_Capita_HH_Inc_1989
## 16 28617
## 17 31826head(popstats38, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 13 Northeast NJ New Jersey 113754 93370 114585
## 14 Northeast NY New York 311984 236975 281569
## 15 Northeast PA Pennsylvania 186692 159073 166771
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 13 35852 81051 205075 10371 19800
## 14 107031 217725 473252 9268 16647
## 15 54486 120527 233162 8548 16880
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 13 40927 26597 30850
## 14 32965 26119 28462
## 15 29069 22195 26864
## Per_Capita_HH_Inc_1989
## 13 39911
## 14 35192
## 15 30003head(popstats39, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 9 South Central AR Arkansas 33400 35406 34139
## 10 South Central LA Louisiana 75092 79365 74236
## 11 South Central OK Oklahoma 41756 47389 46401
## 12 South Central TX Texas 226868 260561 307563
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 9 6232 19099 37128 5356 12214
## 10 16321 51653 87574 6538 15227
## 11 9622 31546 55007 6596 14750
## 12 48575 171608 349952 7538 16708
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 9 21147 15506 21311
## 10 21949 16867 24408
## 11 23577 19502 26033
## 12 27016 20212 27350
## Per_Capita_HH_Inc_1989
## 9 22436
## 10 22681
## 11 25364
## 12 27520head(popstats40, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 4 Southeast AL Alabama 64068 61688 59917
## 5 Southeast FL Florida 106926 120774 183968
## 6 Southeast GA Georgia 91622 89582 107023
## 7 Southeast MS Mississippi 47102 45628 41269
## 8 Southeast SC South Carolina 49182 48631 53003
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 4 11866 33712 68394 6419 13669
## 5 27428 86263 241633 7168 14675
## 6 18082 51550 133794 7346 15033
## 7 6801 20011 37209 5221 12096
## 8 8874 25507 61347 6835 14711
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 4 23597 16773 22374
## 5 27483 22137 27597
## 6 29021 19111 24302
## 7 20136 13935 19675
## 8 26256 16672 22343
## Per_Capita_HH_Inc_1989
## 4 24496
## 5 31346
## 6 29071
## 7 20576
## 8 25373head(popstats41, 6)## Region_Name State_Code State_Name Births_1969 Births_1979 Births_1989
## 1 West CA California 352858 379212 533429
## 2 West HI Hawaii 15750 17568 19051
## 3 West NV Nevada 8902 12293 17894
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969 Median_HH_Inc_1979
## 1 106629 293491 722979 9302 18243
## 2 4262 11869 29427 10675 20473
## 3 2947 10295 27847 9505 18211
## Median_HH_Inc_19689 Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979
## 1 35798 26162 31488
## 2 38829 24418 29381
## 3 31011 25728 32088
## Per_Capita_HH_Inc_1989
## 1 34995
## 2 33633
## 3 32447Plotting the graphs
library("ggpubr")
regionsURL <- ("https://raw.githubusercontent.com/tagensingh/SPS-WRKSHP-R-FINAL-PROJECT/master/Regions_Totals.csv")
regionsURL <- ("Regions_Totals.csv")
regions <- read.table(file =regionsURL, header = TRUE , sep = ",")
summary(regions)## Region X1969.Births X1979.Births X1989.Births
## Length:11 Min. : 93724 Min. : 106689 Min. : 112741
## Class :character 1st Qu.: 204614 1st Qu.: 209594 1st Qu.: 208915
## Mode :character Median : 377116 Median : 400970 Median : 445180
## Mean : 654370 Mean : 636316 Mean : 711597
## 3rd Qu.: 521847 3rd Qu.: 456070 3rd Qu.: 572202
## Max. :3599036 Max. :3499737 Max. :3913786
## X1969.GDP.C.DLS X1979.GDP.C.DLS X1989.GDP.C.DLS X1969.Med.HH.Inc
## Min. : 27444 Min. : 77085 Min. : 160674 Min. : 17421
## 1st Qu.: 54554 1st Qu.: 136252 1st Qu.: 294821 1st Qu.: 30588
## Median : 80750 Median : 272718 Median : 542377 Median : 43915
## Mean :175074 Mean : 452622 Mean : 975651 Mean : 75690
## 3rd Qu.:156641 3rd Qu.: 372925 3rd Qu.: 857598 3rd Qu.: 55403
## Max. :962906 Max. :2489420 Max. :5366083 Max. :416296
## X1979.Med.HH.Inc X1989.Med.HH.Inc X1969.HH.Inc.Per.C.DLS
## Min. : 35147 Min. : 58433 Min. : 47091
## 1st Qu.: 64542 1st Qu.: 114727 1st Qu.: 81770
## Median : 93116 Median : 151614 Median : 118853
## Mean :154218 Mean : 270158 Mean : 197921
## 3rd Qu.:113425 3rd Qu.: 195704 3rd Qu.: 139727
## Max. :848196 Max. :1485868 Max. :1088566
## X1979.HH.Inc.Per.C.DLS X1989.HH.Inc.Per.C.DLS
## Min. : 59332 Min. : 60443
## 1st Qu.: 107696 1st Qu.: 117984
## Median : 153560 Median : 155421
## Mean : 249662 Mean : 272136
## 3rd Qu.: 176708 3rd Qu.: 192343
## Max. :1373139 Max. :1496750names(regions)[1] <- "Region"
names(regions)[2] <- "Births_1969"
names(regions)[3] <- "Births_1979"
names(regions)[4] <- "Births_1989"
names(regions)[5] <- "GDP_1969"
names(regions)[6] <- "GDP_1979"
names(regions)[7] <- "GDP_1989"
names(regions)[8] <- "Median_HH_Inc_1969"
names(regions)[9] <- "Median_HH_Inc_1979"
names(regions)[10] <- "Median_HH_Inc_1989"
names(regions)[11] <- "Per_Capita_HH_Inc_1969"
names(regions)[12] <- "Per_Capita_HH_Inc_1979"
names(regions)[13] <- "Per_Capita_HH_Inc_1989"
print("The Summary Table by Region is as follows")## [1] "The Summary Table by Region is as follows"summary(regions)## Region Births_1969 Births_1979 Births_1989
## Length:11 Min. : 93724 Min. : 106689 Min. : 112741
## Class :character 1st Qu.: 204614 1st Qu.: 209594 1st Qu.: 208915
## Mode :character Median : 377116 Median : 400970 Median : 445180
## Mean : 654370 Mean : 636316 Mean : 711597
## 3rd Qu.: 521847 3rd Qu.: 456070 3rd Qu.: 572202
## Max. :3599036 Max. :3499737 Max. :3913786
## GDP_1969 GDP_1979 GDP_1989 Median_HH_Inc_1969
## Min. : 27444 Min. : 77085 Min. : 160674 Min. : 17421
## 1st Qu.: 54554 1st Qu.: 136252 1st Qu.: 294821 1st Qu.: 30588
## Median : 80750 Median : 272718 Median : 542377 Median : 43915
## Mean :175074 Mean : 452622 Mean : 975651 Mean : 75690
## 3rd Qu.:156641 3rd Qu.: 372925 3rd Qu.: 857598 3rd Qu.: 55403
## Max. :962906 Max. :2489420 Max. :5366083 Max. :416296
## Median_HH_Inc_1979 Median_HH_Inc_1989 Per_Capita_HH_Inc_1969
## Min. : 35147 Min. : 58433 Min. : 47091
## 1st Qu.: 64542 1st Qu.: 114727 1st Qu.: 81770
## Median : 93116 Median : 151614 Median : 118853
## Mean :154218 Mean : 270158 Mean : 197921
## 3rd Qu.:113425 3rd Qu.: 195704 3rd Qu.: 139727
## Max. :848196 Max. :1485868 Max. :1088566
## Per_Capita_HH_Inc_1979 Per_Capita_HH_Inc_1989
## Min. : 59332 Min. : 60443
## 1st Qu.: 107696 1st Qu.: 117984
## Median : 153560 Median : 155421
## Mean : 249662 Mean : 272136
## 3rd Qu.: 176708 3rd Qu.: 192343
## Max. :1373139 Max. :1496750head(regions,12)## Region Births_1969 Births_1979 Births_1989 GDP_1969 GDP_1979 GDP_1989
## 1 Great Lakes 781184 717470 699720 222966 516663 975780
## 2 Midsouth 431264 400970 437329 103824 272718 619108
## 3 Midwest 211976 215478 201226 53581 141754 256985
## 4 Mountain West 150856 203710 216604 32482 113652 233646
## 5 New England 197252 158900 194243 55527 130750 332657
## 6 North West 93724 106689 112741 27444 77085 160674
## 7 Northeast 612430 489418 562925 197369 419303 911489
## 8 South Central 377116 422721 462339 80750 273906 529661
## 9 Southeast 358900 366303 445180 73051 217043 542377
## 10 West 384334 418078 581479 115912 326546 803706
## 11 United States 3599036 3499737 3913786 962906 2489420 5366083
## Median_HH_Inc_1969 Median_HH_Inc_1979 Median_HH_Inc_1989
## 1 55653 109321 181126
## 2 62666 128965 233099
## 3 43915 93116 151614
## 4 55153 117528 186578
## 5 52985 99368 204829
## 6 17421 35147 58433
## 7 28187 53327 102961
## 8 26028 58899 93689
## 9 32989 70184 126493
## 10 41299 82341 147046
## 11 416296 848196 1485868
## Per_Capita_HH_Inc_1969 Per_Capita_HH_Inc_1979 Per_Capita_HH_Inc_1989
## 1 138927.49 170345.50 178357.70
## 2 168752.99 215024.42 245241.31
## 3 118853.19 153559.59 155420.51
## 4 140527.35 183069.69 182426.89
## 5 135510.58 158589.29 202258.87
## 6 47091.00 59331.48 60442.85
## 7 74911.24 86176.79 105105.85
## 8 72087.95 99102.17 98001.83
## 9 88629.53 116290.46 130862.47
## 10 103274.43 131649.08 138631.90
## 11 1088565.74 1373138.47 1496750.19ggscatter(regions, x = "Births_1969", y = "GDP_1969",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1969", ylab = "GDP 1969")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1969", y = "Median_HH_Inc_1969",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1969", ylab = "Median HH Inc 1969")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1969", y = "Per_Capita_HH_Inc_1969",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1969", ylab = "Per Capita HH Inc 1969")## `geom_smooth()` using formula 'y ~ x'
ggscatter(regions, x = "Births_1979", y = "GDP_1979",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1979", ylab = "GDP 1979")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1979", y = "Median_HH_Inc_1979",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1979", ylab = "Median HH Inc 1979")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1979", y = "Per_Capita_HH_Inc_1979",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1979", ylab = "Per Capita HH Inc 1979")## `geom_smooth()` using formula 'y ~ x'
ggscatter(regions, x = "Births_1989", y = "GDP_1989",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1989", ylab = "GDP 1989")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1989", y = "Median_HH_Inc_1989",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1989", ylab = "Median HH Inc 1989")## `geom_smooth()` using formula 'y ~ x'
##
ggscatter(regions, x = "Births_1989", y = "Per_Capita_HH_Inc_1989",
add = "reg.line", conf.int = TRUE,
cor.coef = TRUE, cor.method = "pearson",
xlab = "Births 1989", ylab = "Per Capita HH Inc 1989")## `geom_smooth()` using formula 'y ~ x'
## - Births 1969 to GDP 1969
b1969_g1969 <- cor.test(regions$Births_1969, regions$GDP_1969,
method = "pearson")
b1969_g1969##
## Pearson's product-moment correlation
##
## data: regions$Births_1969 and regions$GDP_1969
## t = 49.725, df = 9, p-value = 2.699e-12
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9927624 0.9995458
## sample estimates:
## cor
## 0.998185## - Births 1969 to Median HH Income 1969
b1969_medhh_1969 <- cor.test(regions$Births_1969, regions$Median_HH_Inc_1969,
method = "pearson")
b1969_medhh_1969##
## Pearson's product-moment correlation
##
## data: regions$Births_1969 and regions$Median_HH_Inc_1969
## t = 13.443, df = 9, p-value = 2.911e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9073386 0.9939410
## sample estimates:
## cor
## 0.9759915## - Births 1969 to GDP Per Capita HH Income
b1969_percaphh1969 <- cor.test(regions$Births_1969, regions$Per_Capita_HH_Inc_1969,
method = "pearson")
b1969_percaphh1969##
## Pearson's product-moment correlation
##
## data: regions$Births_1969 and regions$Per_Capita_HH_Inc_1969
## t = 13.399, df = 9, p-value = 2.995e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9067686 0.9939020
## sample estimates:
## cor
## 0.9758384########
## - Births 1979 to GDP 1979
b1979_g1979 <- cor.test(regions$Births_1979, regions$GDP_1979,
method = "pearson")
b1979_g1979##
## Pearson's product-moment correlation
##
## data: regions$Births_1979 and regions$GDP_1979
## t = 64.869, df = 9, p-value = 2.482e-13
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9957378 0.9997329
## sample estimates:
## cor
## 0.9989323## - Births 1969 to Median HH Income 1969
b1979_medhh_1979 <- cor.test(regions$Births_1979, regions$Median_HH_Inc_1979,
method = "pearson")
b1979_medhh_1979##
## Pearson's product-moment correlation
##
## data: regions$Births_1979 and regions$Median_HH_Inc_1979
## t = 14.636, df = 9, p-value = 1.396e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9209713 0.9948667
## sample estimates:
## cor
## 0.9796316## - Births 1969 to GDP Per Capita HH Income
b1979_percaphh1979 <- cor.test(regions$Births_1979, regions$Per_Capita_HH_Inc_1979,
method = "pearson")
b1979_percaphh1979##
## Pearson's product-moment correlation
##
## data: regions$Births_1979 and regions$Per_Capita_HH_Inc_1979
## t = 14.626, df = 9, p-value = 1.404e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9208747 0.9948602
## sample estimates:
## cor
## 0.9796059#######
## - Births 1979 to GDP 1979
b1989_g1989 <- cor.test(regions$Births_1989, regions$GDP_1989,
method = "pearson")
b1989_g1989##
## Pearson's product-moment correlation
##
## data: regions$Births_1989 and regions$GDP_1989
## t = 66.616, df = 9, p-value = 1.955e-13
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9959577 0.9997467
## sample estimates:
## cor
## 0.9989875## - Births 1989 to Median HH Income 1989
b1989_medhh_1989 <- cor.test(regions$Births_1989, regions$Median_HH_Inc_1989,
method = "pearson")
b1989_medhh_1989##
## Pearson's product-moment correlation
##
## data: regions$Births_1989 and regions$Median_HH_Inc_1989
## t = 14.217, df = 9, p-value = 1.796e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9165398 0.9945671
## sample estimates:
## cor
## 0.9784525## - Births 1989 to GDP Per Capita HH Income
b1989_percaphh1989 <- cor.test(regions$Births_1989, regions$Per_Capita_HH_Inc_1989,
method = "pearson")
b1989_percaphh1989##
## Pearson's product-moment correlation
##
## data: regions$Births_1989 and regions$Per_Capita_HH_Inc_1989
## t = 14.133, df = 9, p-value = 1.89e-07
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.9156109 0.9945042
## sample estimates:
## cor
## 0.9782049