CMS Data Exercise Part 1

This is an exercise for an interview for the company of Clipboard Health, dataset can be downloaded at the site: Data.CMS.gov

We can observe that the dataset consists of attributes such as provider, city, state, county, and hours worked for the occupations of CNA, LPN, and RN. For this study, we will focus on the first quarter of 2024. We are interested in exploring the measures of central tendency and measures of spread based on the geography. Theoretically, we could explore how hours worked depends on the demographics of the population including gender, age, and nationality, but for simplicity, we will focus on geography.

## # A tibble: 6 × 38
##   Provnum Provname       City  State County_Name County_Fips `City,State,County`
##   <chr>   <chr>          <chr> <chr> <chr>             <dbl> <chr>              
## 1 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## 2 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## 3 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## 4 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## 5 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## 6 435088  CENTERVILLE C… CENT… SD    Turner              125 centerville,sd,tur…
## # ℹ 31 more variables: Density <dbl>, CY_Qtr <chr>, WorkDate <dbl>,
## #   MDScensus <dbl>, Hrs_RNDON <dbl>, Hrs_RNDON_emp <dbl>, Hrs_RNDON_ctr <dbl>,
## #   Hrs_RNadmin <dbl>, Hrs_RNadmin_emp <dbl>, Hrs_RNadmin_ctr <dbl>,
## #   Hrs_RN_Density <dbl>, Hrs_RN <dbl>, Hrs_RN_emp <dbl>, Hrs_RN_ctr <dbl>,
## #   Hrs_LPNadmin <dbl>, Hrs_LPNadmin_emp <dbl>, Hrs_LPNadmin_ctr <dbl>,
## #   Hrs_LPN_Density <chr>, Hrs_LPN <dbl>, Hrs_LPN_emp <dbl>, Hrs_LPN_ctr <dbl>,
## #   Hrs_CNA_Density <chr>, Hrs_CNA <dbl>, Hrs_CNA_emp <dbl>, …
## Rows: 1,048,575
## Columns: 38
## $ Provnum             <chr> "15009", "15009", "15009", "15009", "15009", "1500…
## $ Provname            <chr> "BURNS NURSING HOME, INC.", "BURNS NURSING HOME, I…
## $ City                <chr> "RUSSELLVILLE", "RUSSELLVILLE", "RUSSELLVILLE", "R…
## $ State               <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "AL", "A…
## $ County_Name         <chr> "Franklin", "Franklin", "Franklin", "Franklin", "F…
## $ County_Fips         <dbl> 59, 59, 59, 59, 59, 59, 59, 59, 59, 59, 59, 59, 59…
## $ `City,State,County` <chr> "russellville,al,franklin", "russellville,al,frank…
## $ Density             <dbl> 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30…
## $ CY_Qtr              <chr> "2024Q1", "2024Q1", "2024Q1", "2024Q1", "2024Q1", …
## $ WorkDate            <dbl> 20240101, 20240102, 20240103, 20240104, 20240105, …
## $ MDScensus           <dbl> 50, 49, 49, 50, 51, 51, 51, 52, 52, 50, 50, 49, 48…
## $ Hrs_RNDON           <dbl> 8.00, 8.00, 8.00, 8.00, 8.00, 0.00, 0.00, 10.77, 8…
## $ Hrs_RNDON_emp       <dbl> 8.00, 8.00, 8.00, 8.00, 8.00, 0.00, 0.00, 10.77, 8…
## $ Hrs_RNDON_ctr       <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_RNadmin         <dbl> 8.00, 18.24, 15.10, 14.90, 15.47, 0.00, 0.00, 16.6…
## $ Hrs_RNadmin_emp     <dbl> 8.00, 18.24, 15.10, 14.90, 15.47, 0.00, 0.00, 16.6…
## $ Hrs_RNadmin_ctr     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_RN_Density      <dbl> 1.336, 1.963, 1.834, 1.904, 1.559, 0.908, 1.228, 1…
## $ Hrs_RN              <dbl> 40.07, 58.89, 55.02, 57.13, 46.76, 27.23, 36.84, 4…
## $ Hrs_RN_emp          <dbl> 40.07, 58.89, 55.02, 57.13, 46.76, 27.23, 36.84, 4…
## $ Hrs_RN_ctr          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_LPNadmin        <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_LPNadmin_emp    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_LPNadmin_ctr    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_LPN_Density     <chr> "0.605", "0.765", "0.690", "0.423", "0.915", "0.55…
## $ Hrs_LPN             <dbl> 18.16, 22.96, 20.70, 12.70, 27.44, 16.78, 15.64, 3…
## $ Hrs_LPN_emp         <dbl> 18.16, 22.96, 20.70, 12.70, 27.44, 16.78, 15.64, 3…
## $ Hrs_LPN_ctr         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_CNA_Density     <chr> "5.211", "4.980", "4.905", "4.740", "4.980", "4.67…
## $ Hrs_CNA             <dbl> 156.34, 149.40, 147.15, 142.21, 149.40, 140.12, 12…
## $ Hrs_CNA_emp         <dbl> 156.34, 149.40, 147.15, 142.21, 149.40, 140.12, 12…
## $ Hrs_CNA_ctr         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_NAtrn           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_NAtrn_emp       <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_NAtrn_ctr       <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_MedAide         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_MedAide_emp     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ Hrs_MedAide_ctr     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## spc_tbl_ [1,048,575 × 38] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
##  $ Provnum          : chr [1:1048575] "15009" "15009" "15009" "15009" ...
##  $ Provname         : chr [1:1048575] "BURNS NURSING HOME, INC." "BURNS NURSING HOME, INC." "BURNS NURSING HOME, INC." "BURNS NURSING HOME, INC." ...
##  $ City             : chr [1:1048575] "RUSSELLVILLE" "RUSSELLVILLE" "RUSSELLVILLE" "RUSSELLVILLE" ...
##  $ State            : chr [1:1048575] "AL" "AL" "AL" "AL" ...
##  $ County_Name      : chr [1:1048575] "Franklin" "Franklin" "Franklin" "Franklin" ...
##  $ County_Fips      : num [1:1048575] 59 59 59 59 59 59 59 59 59 59 ...
##  $ City,State,County: chr [1:1048575] "russellville,al,franklin" "russellville,al,franklin" "russellville,al,franklin" "russellville,al,franklin" ...
##  $ Density          : num [1:1048575] 30 30 30 30 30 30 30 30 30 30 ...
##  $ CY_Qtr           : chr [1:1048575] "2024Q1" "2024Q1" "2024Q1" "2024Q1" ...
##  $ WorkDate         : num [1:1048575] 20240101 20240102 20240103 20240104 20240105 ...
##  $ MDScensus        : num [1:1048575] 50 49 49 50 51 51 51 52 52 50 ...
##  $ Hrs_RNDON        : num [1:1048575] 8 8 8 8 8 ...
##  $ Hrs_RNDON_emp    : num [1:1048575] 8 8 8 8 8 ...
##  $ Hrs_RNDON_ctr    : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_RNadmin      : num [1:1048575] 8 18.2 15.1 14.9 15.5 ...
##  $ Hrs_RNadmin_emp  : num [1:1048575] 8 18.2 15.1 14.9 15.5 ...
##  $ Hrs_RNadmin_ctr  : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_RN_Density   : num [1:1048575] 1.34 1.96 1.83 1.9 1.56 ...
##  $ Hrs_RN           : num [1:1048575] 40.1 58.9 55 57.1 46.8 ...
##  $ Hrs_RN_emp       : num [1:1048575] 40.1 58.9 55 57.1 46.8 ...
##  $ Hrs_RN_ctr       : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_LPNadmin     : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_LPNadmin_emp : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_LPNadmin_ctr : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_LPN_Density  : chr [1:1048575] "0.605" "0.765" "0.690" "0.423" ...
##  $ Hrs_LPN          : num [1:1048575] 18.2 23 20.7 12.7 27.4 ...
##  $ Hrs_LPN_emp      : num [1:1048575] 18.2 23 20.7 12.7 27.4 ...
##  $ Hrs_LPN_ctr      : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_CNA_Density  : chr [1:1048575] "5.211" "4.980" "4.905" "4.740" ...
##  $ Hrs_CNA          : num [1:1048575] 156 149 147 142 149 ...
##  $ Hrs_CNA_emp      : num [1:1048575] 156 149 147 142 149 ...
##  $ Hrs_CNA_ctr      : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_NAtrn        : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_NAtrn_emp    : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_NAtrn_ctr    : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_MedAide      : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_MedAide_emp  : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  $ Hrs_MedAide_ctr  : num [1:1048575] 0 0 0 0 0 0 0 0 0 0 ...
##  - attr(*, "spec")=
##   .. cols(
##   ..   Provnum = col_character(),
##   ..   Provname = col_character(),
##   ..   City = col_character(),
##   ..   State = col_character(),
##   ..   County_Name = col_character(),
##   ..   County_Fips = col_double(),
##   ..   `City,State,County` = col_character(),
##   ..   Density = col_double(),
##   ..   CY_Qtr = col_character(),
##   ..   WorkDate = col_double(),
##   ..   MDScensus = col_double(),
##   ..   Hrs_RNDON = col_double(),
##   ..   Hrs_RNDON_emp = col_double(),
##   ..   Hrs_RNDON_ctr = col_double(),
##   ..   Hrs_RNadmin = col_double(),
##   ..   Hrs_RNadmin_emp = col_double(),
##   ..   Hrs_RNadmin_ctr = col_double(),
##   ..   Hrs_RN_Density = col_double(),
##   ..   Hrs_RN = col_double(),
##   ..   Hrs_RN_emp = col_double(),
##   ..   Hrs_RN_ctr = col_double(),
##   ..   Hrs_LPNadmin = col_double(),
##   ..   Hrs_LPNadmin_emp = col_double(),
##   ..   Hrs_LPNadmin_ctr = col_double(),
##   ..   Hrs_LPN_Density = col_character(),
##   ..   Hrs_LPN = col_double(),
##   ..   Hrs_LPN_emp = col_double(),
##   ..   Hrs_LPN_ctr = col_double(),
##   ..   Hrs_CNA_Density = col_character(),
##   ..   Hrs_CNA = col_double(),
##   ..   Hrs_CNA_emp = col_double(),
##   ..   Hrs_CNA_ctr = col_double(),
##   ..   Hrs_NAtrn = col_double(),
##   ..   Hrs_NAtrn_emp = col_double(),
##   ..   Hrs_NAtrn_ctr = col_double(),
##   ..   Hrs_MedAide = col_double(),
##   ..   Hrs_MedAide_emp = col_double(),
##   ..   Hrs_MedAide_ctr = col_double()
##   .. )
##  - attr(*, "problems")=<externalptr>
##    Provnum            Provname             City              State          
##  Length:1048575     Length:1048575     Length:1048575     Length:1048575    
##  Class :character   Class :character   Class :character   Class :character  
##  Mode  :character   Mode  :character   Mode  :character   Mode  :character  
##                                                                             
##                                                                             
##                                                                             
##                                                                             
##  County_Name         County_Fips     City,State,County     Density       
##  Length:1048575     Min.   :  1.00   Length:1048575     Min.   :    0.0  
##  Class :character   1st Qu.: 27.00   Class :character   1st Qu.:   32.7  
##  Mode  :character   Median : 65.00   Mode  :character   Median :  152.3  
##                     Mean   : 74.76                      Mean   :  894.5  
##                     3rd Qu.:109.00                      3rd Qu.:  775.4  
##                     Max.   :510.00                      Max.   :34729.8  
##                                                         NA's   :86541    
##     CY_Qtr             WorkDate          MDScensus        Hrs_RNDON      
##  Length:1048575     Min.   :20240101   Min.   :  0.00   Min.   :  0.000  
##  Class :character   1st Qu.:20240123   1st Qu.: 52.00   1st Qu.:  0.000  
##  Mode  :character   Median :20240215   Median : 78.00   Median :  8.000  
##                     Mean   :20240216   Mean   : 85.79   Mean   :  5.209  
##                     3rd Qu.:20240309   3rd Qu.:107.00   3rd Qu.:  8.000  
##                     Max.   :20240331   Max.   :743.00   Max.   :327.750  
##                                                                          
##  Hrs_RNDON_emp     Hrs_RNDON_ctr       Hrs_RNadmin     Hrs_RNadmin_emp 
##  Min.   :  0.000   Min.   : 0.00000   Min.   :  0.00   Min.   :  0.00  
##  1st Qu.:  0.000   1st Qu.: 0.00000   1st Qu.:  0.00   1st Qu.:  0.00  
##  Median :  8.000   Median : 0.00000   Median :  8.00   Median :  7.75  
##  Mean   :  5.118   Mean   : 0.09086   Mean   : 10.95   Mean   : 10.68  
##  3rd Qu.:  8.000   3rd Qu.: 0.00000   3rd Qu.: 16.00   3rd Qu.: 16.00  
##  Max.   :327.750   Max.   :42.00000   Max.   :266.15   Max.   :266.15  
##                                                                        
##  Hrs_RNadmin_ctr   Hrs_RN_Density       Hrs_RN         Hrs_RN_emp    
##  Min.   : 0.0000   Min.   :  0.00   Min.   :  0.00   Min.   :  0.00  
##  1st Qu.: 0.0000   1st Qu.:  0.03   1st Qu.: 14.22   1st Qu.: 12.25  
##  Median : 0.0000   Median :  0.14   Median : 27.00   Median : 24.79  
##  Mean   : 0.2721   Mean   :  0.98   Mean   : 36.24   Mean   : 32.86  
##  3rd Qu.: 0.0000   3rd Qu.:  0.64   3rd Qu.: 47.25   3rd Qu.: 43.25  
##  Max.   :92.5000   Max.   :308.75   Max.   :908.62   Max.   :904.15  
##                    NA's   :90454                                     
##    Hrs_RN_ctr       Hrs_LPNadmin     Hrs_LPNadmin_emp  Hrs_LPNadmin_ctr   
##  Min.   :  0.000   Min.   :  0.000   Min.   :  0.000   Min.   :  0.00000  
##  1st Qu.:  0.000   1st Qu.:  0.000   1st Qu.:  0.000   1st Qu.:  0.00000  
##  Median :  0.000   Median :  0.000   Median :  0.000   Median :  0.00000  
##  Mean   :  3.377   Mean   :  6.161   Mean   :  6.083   Mean   :  0.07852  
##  3rd Qu.:  0.000   3rd Qu.:  8.320   3rd Qu.:  8.250   3rd Qu.:  0.00000  
##  Max.   :430.590   Max.   :154.370   Max.   :152.000   Max.   :154.37000  
##                                                                           
##  Hrs_LPN_Density       Hrs_LPN        Hrs_LPN_emp      Hrs_LPN_ctr     
##  Length:1048575     Min.   :  0.00   Min.   :  0.00   Min.   :  0.000  
##  Class :character   1st Qu.: 32.26   1st Qu.: 27.60   1st Qu.:  0.000  
##  Mode  :character   Median : 57.06   Median : 50.50   Median :  0.000  
##                     Mean   : 66.81   Mean   : 59.81   Mean   :  6.994  
##                     3rd Qu.: 89.60   3rd Qu.: 81.42   3rd Qu.:  7.000  
##                     Max.   :614.65   Max.   :603.98   Max.   :454.000  
##                                                                        
##  Hrs_CNA_Density       Hrs_CNA        Hrs_CNA_emp       Hrs_CNA_ctr    
##  Length:1048575     Min.   :   0.0   Min.   :   0.00   Min.   :  0.00  
##  Class :character   1st Qu.: 100.2   1st Qu.:  90.72   1st Qu.:  0.00  
##  Mode  :character   Median : 154.8   Median : 142.09   Median :  0.00  
##                     Mean   : 177.7   Mean   : 163.74   Mean   : 13.97  
##                     3rd Qu.: 224.9   3rd Qu.: 210.65   3rd Qu.: 12.00  
##                     Max.   :1857.7   Max.   :1573.08   Max.   :694.30  
##                                                                        
##    Hrs_NAtrn       Hrs_NAtrn_emp     Hrs_NAtrn_ctr        Hrs_MedAide     
##  Min.   :  0.000   Min.   :  0.000   Min.   :  0.00000   Min.   :  0.000  
##  1st Qu.:  0.000   1st Qu.:  0.000   1st Qu.:  0.00000   1st Qu.:  0.000  
##  Median :  0.000   Median :  0.000   Median :  0.00000   Median :  0.000  
##  Mean   :  3.997   Mean   :  3.927   Mean   :  0.07074   Mean   :  8.657  
##  3rd Qu.:  0.000   3rd Qu.:  0.000   3rd Qu.:  0.00000   3rd Qu.:  9.250  
##  Max.   :452.000   Max.   :279.020   Max.   :280.50000   Max.   :395.650  
##                                                                           
##  Hrs_MedAide_emp  Hrs_MedAide_ctr   
##  Min.   :  0.00   Min.   :  0.0000  
##  1st Qu.:  0.00   1st Qu.:  0.0000  
##  Median :  0.00   Median :  0.0000  
##  Mean   :  8.41   Mean   :  0.2465  
##  3rd Qu.:  8.50   3rd Qu.:  0.0000  
##  Max.   :395.65   Max.   :128.9000  
##
Data summary
Name Piped data
Number of rows 1048575
Number of columns 29
_______________________
Column type frequency:
numeric 29
________________________
Group variables None

Variable type: numeric

skim_variable complete_rate mean sd p0 p25 p50 p75 p100 hist
County_Fips 1.00 74.76 61.75 1 27.00 65.00 109.00 510.00 ▇▃▁▁▁
Density 0.92 894.48 2160.39 0 32.70 152.30 775.40 34729.80 ▇▁▁▁▁
WorkDate 1.00 20240215.68 83.01 20240101 20240123.00 20240215.00 20240309.00 20240331.00 ▇▁▇▁▇
MDScensus 1.00 85.79 51.54 0 52.00 78.00 107.00 743.00 ▇▁▁▁▁
Hrs_RNDON 1.00 5.21 4.63 0 0.00 8.00 8.00 327.75 ▇▁▁▁▁
Hrs_RNDON_emp 1.00 5.12 4.63 0 0.00 8.00 8.00 327.75 ▇▁▁▁▁
Hrs_RNDON_ctr 1.00 0.09 0.89 0 0.00 0.00 0.00 42.00 ▇▁▁▁▁
Hrs_RNadmin 1.00 10.95 15.55 0 0.00 8.00 16.00 266.15 ▇▁▁▁▁
Hrs_RNadmin_emp 1.00 10.68 15.30 0 0.00 7.75 16.00 266.15 ▇▁▁▁▁
Hrs_RNadmin_ctr 1.00 0.27 1.97 0 0.00 0.00 0.00 92.50 ▇▁▁▁▁
Hrs_RN_Density 0.91 0.98 4.22 0 0.03 0.14 0.64 308.75 ▇▁▁▁▁
Hrs_RN 1.00 36.24 36.67 0 14.23 27.00 47.25 908.62 ▇▁▁▁▁
Hrs_RN_emp 1.00 32.86 32.94 0 12.25 24.79 43.25 904.15 ▇▁▁▁▁
Hrs_RN_ctr 1.00 3.38 11.67 0 0.00 0.00 0.00 430.59 ▇▁▁▁▁
Hrs_LPNadmin 1.00 6.16 10.29 0 0.00 0.00 8.32 154.37 ▇▁▁▁▁
Hrs_LPNadmin_emp 1.00 6.08 10.18 0 0.00 0.00 8.25 152.00 ▇▁▁▁▁
Hrs_LPNadmin_ctr 1.00 0.08 1.39 0 0.00 0.00 0.00 154.37 ▇▁▁▁▁
Hrs_LPN 1.00 66.81 49.38 0 32.26 57.06 89.60 614.65 ▇▁▁▁▁
Hrs_LPN_emp 1.00 59.81 45.26 0 27.60 50.50 81.42 603.98 ▇▁▁▁▁
Hrs_LPN_ctr 1.00 6.99 17.05 0 0.00 0.00 7.00 454.00 ▇▁▁▁▁
Hrs_CNA 1.00 177.71 118.68 0 100.18 154.75 224.90 1857.74 ▇▁▁▁▁
Hrs_CNA_emp 1.00 163.74 110.46 0 90.72 142.09 210.65 1573.08 ▇▁▁▁▁
Hrs_CNA_ctr 1.00 13.97 34.57 0 0.00 0.00 12.00 694.30 ▇▁▁▁▁
Hrs_NAtrn 1.00 4.00 12.87 0 0.00 0.00 0.00 452.00 ▇▁▁▁▁
Hrs_NAtrn_emp 1.00 3.93 12.41 0 0.00 0.00 0.00 279.02 ▇▁▁▁▁
Hrs_NAtrn_ctr 1.00 0.07 2.32 0 0.00 0.00 0.00 280.50 ▇▁▁▁▁
Hrs_MedAide 1.00 8.66 18.62 0 0.00 0.00 9.25 395.65 ▇▁▁▁▁
Hrs_MedAide_emp 1.00 8.41 18.17 0 0.00 0.00 8.50 395.65 ▇▁▁▁▁
Hrs_MedAide_ctr 1.00 0.25 2.36 0 0.00 0.00 0.00 128.90 ▇▁▁▁▁ 
## [1] "--- Summarizing key statistics based on State ---"
## [1] "--- Summarizing key statistics based on Provider ---"
Data summary
Name Piped data
Number of rows 31941
Number of columns 29
_______________________
Column type frequency:
numeric 29
________________________
Group variables None

Variable type: numeric

Data summary
skim_variable complete_rate mean sd p0 p25 p50 p75 p100 hist
County_Fips 1.00 144.80 88.65 1.0 67.00 127.00 215.00 321.00 ▆▇▅▃▅
Density 0.88 258.41 367.08 2.8 23.20 82.00 337.60 1741.40 ▇▁▁▁▁
WorkDate 1.00 20240215.68 83.01 20240101.0 20240123.00 20240215.00 20240309.00 20240331.00 ▇▁▇▁▇
MDScensus 1.00 86.91 38.90 2.0 60.00 80.00 105.00 276.00 ▂▇▂▁▁
Hrs_RNDON 1.00 5.21 4.27 0.0 0.00 8.00 8.00 24.00 ▅▇▁▁▁
Hrs_RNDON_emp 1.00 5.16 4.28 0.0 0.00 8.00 8.00 24.00 ▆▇▁▁▁
Hrs_RNDON_ctr 1.00 0.05 0.66 0.0 0.00 0.00 0.00 19.75 ▇▁▁▁▁
Hrs_RNadmin 1.00 8.83 10.32 0.0 0.00 7.75 15.94 68.25 ▇▂▁▁▁
Hrs_RNadmin_emp 1.00 8.76 10.27 0.0 0.00 7.72 15.83 68.25 ▇▂▁▁▁
Hrs_RNadmin_ctr 1.00 0.07 0.78 0.0 0.00 0.00 0.00 18.00 ▇▁▁▁▁
Hrs_RN_Density 0.88 0.48 0.88 0.0 0.04 0.15 0.55 13.54 ▇▁▁▁▁
Hrs_RN 1.00 22.74 20.28 0.0 8.52 18.25 31.83 272.86 ▇▁▁▁▁
Hrs_RN_emp 1.00 21.70 20.16 0.0 8.25 16.95 30.75 272.86 ▇▁▁▁▁
Hrs_RN_ctr 1.00 1.04 4.85 0.0 0.00 0.00 0.00 64.25 ▇▁▁▁▁
Hrs_LPNadmin 1.00 6.42 10.30 0.0 0.00 0.00 8.96 119.39 ▇▁▁▁▁
Hrs_LPNadmin_emp 1.00 6.40 10.24 0.0 0.00 0.00 8.95 119.39 ▇▁▁▁▁
Hrs_LPNadmin_ctr 1.00 0.02 0.39 0.0 0.00 0.00 0.00 16.50 ▇▁▁▁▁
Hrs_LPN 1.00 77.72 43.81 0.0 47.00 67.59 99.75 321.99 ▇▇▂▁▁
Hrs_LPN_emp 1.00 71.88 42.63 0.0 42.89 62.15 93.50 321.99 ▇▆▁▁▁
Hrs_LPN_ctr 1.00 5.84 15.95 0.0 0.00 0.00 0.00 133.75 ▇▁▁▁▁
Hrs_CNA 1.00 161.40 83.11 0.0 104.55 143.96 200.86 777.12 ▇▆▁▁▁
Hrs_CNA_emp 1.00 148.72 79.73 0.0 95.29 133.70 189.25 527.81 ▅▇▂▁▁
Hrs_CNA_ctr 1.00 12.68 37.04 0.0 0.00 0.00 0.00 360.00 ▇▁▁▁▁
Hrs_NAtrn 1.00 1.00 5.99 0.0 0.00 0.00 0.00 107.90 ▇▁▁▁▁
Hrs_NAtrn_emp 1.00 1.00 5.99 0.0 0.00 0.00 0.00 107.90 ▇▁▁▁▁
Hrs_NAtrn_ctr 1.00 0.00 0.07 0.0 0.00 0.00 0.00 11.72 ▇▁▁▁▁
Hrs_MedAide 1.00 13.88 24.03 0.0 0.00 0.00 22.05 184.86 ▇▁▁▁▁
Hrs_MedAide_emp 1.00 13.80 24.03 0.0 0.00 0.00 21.78 184.86 ▇▁▁▁▁
Hrs_MedAide_ctr 1.00 0.07 1.13 0.0 0.00 0.00 0.00 35.90 ▇▁▁▁▁
Name Piped data
Number of rows 62790
Number of columns 29
_______________________
Column type frequency:
numeric 29
________________________
Group variables None

Variable type: numeric

skim_variable complete_rate mean sd p0 p25 p50 p75 p100 hist
County_Fips 1.00 74.62 37.08 1 37.00 86.00 103.00 133.00 ▃▂▂▇▃
Density 0.92 721.97 735.14 0 59.70 473.65 1190.40 3641.60 ▇▃▂▁▁
WorkDate 1.00 20240215.68 83.01 20240101 20240123.00 20240215.00 20240309.00 20240331.00 ▇▁▇▁▇
MDScensus 1.00 106.25 43.46 0 85.00 107.00 119.00 390.00 ▃▇▁▁▁
Hrs_RNDON 1.00 5.49 4.59 0 0.00 8.00 8.00 49.20 ▇▁▁▁▁
Hrs_RNDON_emp 1.00 5.45 4.59 0 0.00 8.00 8.00 49.20 ▇▁▁▁▁
Hrs_RNDON_ctr 1.00 0.04 0.61 0 0.00 0.00 0.00 22.20 ▇▁▁▁▁
Hrs_RNadmin 1.00 14.16 14.73 0 0.00 10.00 24.00 140.00 ▇▁▁▁▁
Hrs_RNadmin_emp 1.00 13.99 14.70 0 0.00 9.48 23.62 140.00 ▇▁▁▁▁
Hrs_RNadmin_ctr 1.00 0.18 1.54 0 0.00 0.00 0.00 43.14 ▇▁▁▁▁
Hrs_RN_Density 0.88 1.28 6.77 0 0.04 0.08 0.36 132.21 ▇▁▁▁▁
Hrs_RN 1.00 51.48 39.74 0 25.44 42.72 65.82 493.00 ▇▁▁▁▁
Hrs_RN_emp 1.00 49.76 39.30 0 24.57 41.25 63.91 493.00 ▇▁▁▁▁
Hrs_RN_ctr 1.00 1.72 8.79 0 0.00 0.00 0.00 201.13 ▇▁▁▁▁
Hrs_LPNadmin 1.00 6.60 10.26 0 0.00 0.00 9.00 124.25 ▇▁▁▁▁
Hrs_LPNadmin_emp 1.00 6.58 10.24 0 0.00 0.00 8.97 124.25 ▇▁▁▁▁
Hrs_LPNadmin_ctr 1.00 0.03 0.55 0 0.00 0.00 0.00 29.33 ▇▁▁▁▁
Hrs_LPN 1.00 78.03 42.42 0 48.25 74.96 102.50 452.61 ▇▅▁▁▁
Hrs_LPN_emp 1.00 73.56 40.32 0 45.73 71.14 96.50 452.61 ▇▃▁▁▁
Hrs_LPN_ctr 1.00 4.47 12.47 0 0.00 0.00 0.00 167.50 ▇▁▁▁▁
Hrs_CNA 1.00 240.97 107.29 0 183.25 231.50 280.75 1333.85 ▇▃▁▁▁
Hrs_CNA_emp 1.00 235.59 106.79 0 176.75 227.94 274.95 1333.85 ▇▃▁▁▁
Hrs_CNA_ctr 1.00 5.38 22.85 0 0.00 0.00 0.00 432.20 ▇▁▁▁▁
Hrs_NAtrn 1.00 2.31 10.09 0 0.00 0.00 0.00 206.50 ▇▁▁▁▁
Hrs_NAtrn_emp 1.00 2.31 10.09 0 0.00 0.00 0.00 206.50 ▇▁▁▁▁
Hrs_NAtrn_ctr 1.00 0.00 0.00 0 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_MedAide 1.00 0.10 1.95 0 0.00 0.00 0.00 67.27 ▇▁▁▁▁
Hrs_MedAide_emp 1.00 0.09 1.91 0 0.00 0.00 0.00 67.27 ▇▁▁▁▁
Hrs_MedAide_ctr 1.00 0.01 0.37 0 0.00 0.00 0.00 19.00 ▇▁▁▁▁

skim_type

skim_variable

n_missing

complete_rate

character.min

character.max

character.empty

character.n_unique

character.whitespace

numeric.mean

numeric.sd

numeric.p0

numeric.p25

numeric.p50

numeric.p75

numeric.p100

numeric.hist

character

Provnum

0

1.0000000

6

6

0

18

0

character

Provname

0

1.0000000

19

45

0

18

0

character

City

0

1.0000000

7

12

0

5

0

character

State

0

1.0000000

2

2

0

1

0

character

County_Name

0

1.0000000

6

6

0

1

0

character

City,State,County

0

1.0000000

17

22

0

5

0

character

CY_Qtr

0

1.0000000

6

6

0

1

0

character

Hrs_LPN_Density

0

1.0000000

5

7

0

377

0

character

Hrs_CNA_Density

0

1.0000000

5

7

0

616

0

numeric

County_Fips

0

1.0000000

121.00000000

0.00000000

121.00

121.0000

121.000

121.0000

121.000

▁▁▇▁▁

numeric

Density

182

0.8888889

840.76250000

260.60464474

177.00

956.4000

956.400

956.4000

956.400

▁▁▁▁▇

numeric

WorkDate

0

1.0000000

20,240,215.68131868

83.03268137

20,240,101.00

20,240,123.0000

20,240,215.000

20,240,309.0000

20,240,331.000

▇▁▇▁▇

numeric

MDScensus

0

1.0000000

124.60073260

59.13454875

21.00

86.0000

106.000

172.0000

276.000

▂▇▂▃▁

numeric

Hrs_RNDON

0

1.0000000

5.43192918

4.08299801

0.00

0.0000

8.000

8.0000

16.500

▅▁▇▁▁

numeric

Hrs_RNDON_emp

0

1.0000000

5.43192918

4.08299801

0.00

0.0000

8.000

8.0000

16.500

▅▁▇▁▁

numeric

Hrs_RNDON_ctr

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

numeric

Hrs_RNadmin

0

1.0000000

10.56012210

11.56370613

0.00

0.0000

8.000

17.7500

51.250

▇▂▂▁▁

numeric

Hrs_RNadmin_emp

0

1.0000000

10.56012210

11.56370613

0.00

0.0000

8.000

17.7500

51.250

▇▂▂▁▁

numeric

Hrs_RNadmin_ctr

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

numeric

Hrs_RN_Density

182

0.8888889

0.04113393

0.04942903

0.00

0.0130

0.025

0.0470

0.318

▇▁▁▁▁

numeric

Hrs_RN

0

1.0000000

25.91705739

21.55218970

0.00

11.0000

20.500

36.3000

114.430

▇▅▂▁▁

numeric

Hrs_RN_emp

0

1.0000000

23.20793651

19.54336306

0.00

8.8000

18.500

32.6075

111.000

▇▃▂▁▁

numeric

Hrs_RN_ctr

0

1.0000000

2.70912088

7.22572432

0.00

0.0000

0.000

0.0000

49.290

▇▁▁▁▁

numeric

Hrs_LPNadmin

0

1.0000000

9.60446886

10.82510942

0.00

0.0000

8.000

16.3500

52.300

▇▃▂▁▁

numeric

Hrs_LPNadmin_emp

0

1.0000000

9.57516484

10.84023996

0.00

0.0000

8.000

16.3500

52.300

▇▃▂▁▁

numeric

Hrs_LPNadmin_ctr

0

1.0000000

0.02930403

0.48344203

0.00

0.0000

0.000

0.0000

8.000

▇▁▁▁▁

numeric

Hrs_LPN

0

1.0000000

110.06409035

58.84075048

0.00

65.5300

101.260

151.5975

296.890

▅▇▅▂▁

numeric

Hrs_LPN_emp

0

1.0000000

91.94793651

54.47844658

0.00

50.2500

86.875

120.5550

296.890

▆▇▃▁▁

numeric

Hrs_LPN_ctr

0

1.0000000

18.11615385

26.90302533

0.00

0.0000

0.000

25.5000

123.430

▇▁▁▁▁

numeric

Hrs_CNA

0

1.0000000

245.48927350

133.97242796

33.25

144.8125

220.875

310.5800

777.120

▇▇▂▁▁

numeric

Hrs_CNA_emp

0

1.0000000

192.62713675

109.55882360

0.00

122.5000

152.345

273.2075

510.840

▂▇▂▂▁

numeric

Hrs_CNA_ctr

0

1.0000000

52.86213675

77.03324398

0.00

0.0000

0.000

86.1875

319.540

▇▁▁▁▁

numeric

Hrs_NAtrn

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

numeric

Hrs_NAtrn_emp

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

numeric

Hrs_NAtrn_ctr

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

numeric

Hrs_MedAide

0

1.0000000

19.57255800

28.62610468

0.00

0.0000

0.000

33.5000

153.000

▇▂▁▁▁

numeric

Hrs_MedAide_emp

0

1.0000000

19.57255800

28.62610468

0.00

0.0000

0.000

33.5000

153.000

▇▂▁▁▁

numeric

Hrs_MedAide_ctr

0

1.0000000

0.00000000

0.00000000

0.00

0.0000

0.000

0.0000

0.000

▁▁▇▁▁

skim_type

skim_variable

n_missing

complete_rate

character.min

character.max

character.empty

character.n_unique

character.whitespace

numeric.mean

numeric.sd

numeric.p0

numeric.p25

numeric.p50

numeric.p75

numeric.p100

numeric.hist

character

Provnum

0

1.0000000

6

6

0

11

0

character

Provname

0

1.0000000

21

47

0

11

0

character

City

0

1.0000000

6

14

0

6

0

character

State

0

1.0000000

2

2

0

1

0

character

County_Name

0

1.0000000

8

8

0

1

0

character

City,State,County

0

1.0000000

18

26

0

6

0

character

CY_Qtr

0

1.0000000

6

6

0

1

0

character

Hrs_LPN_Density

0

1.0000000

5

7

0

346

0

character

Hrs_CNA_Density

0

1.0000000

5

7

0

488

0

numeric

County_Fips

0

1.0000000

135.0000000

0.0000000

135.00

135.000

135.000

135.000

135.000

▁▁▇▁▁

numeric

Density

91

0.9090909

469.4700000

217.1433735

29.00

345.800

465.750

640.200

830.700

▂▇▁▇▂

numeric

WorkDate

0

1.0000000

20,240,215.6813187

83.0488250

20,240,101.00

20,240,123.000

20,240,215.000

20,240,309.000

20,240,331.000

▇▁▇▁▇

numeric

MDScensus

0

1.0000000

86.3026973

37.2790462

28.00

59.000

90.000

109.000

164.000

▅▆▇▃▂

numeric

Hrs_RNDON

0

1.0000000

5.8866134

4.2516505

0.00

0.000

8.000

8.000

19.800

▅▁▇▁▁

numeric

Hrs_RNDON_emp

0

1.0000000

5.8866134

4.2516505

0.00

0.000

8.000

8.000

19.800

▅▁▇▁▁

numeric

Hrs_RNDON_ctr

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_RNadmin

0

1.0000000

10.0052248

11.0883642

0.00

0.000

8.000

16.000

57.250

▇▃▁▁▁

numeric

Hrs_RNadmin_emp

0

1.0000000

10.0052248

11.0883642

0.00

0.000

8.000

16.000

57.250

▇▃▁▁▁

numeric

Hrs_RNadmin_ctr

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_RN_Density

91

0.9090909

0.2418582

0.5607612

0.00

0.047

0.079

0.116

2.974

▇▁▁▁▁

numeric

Hrs_RN

0

1.0000000

36.0323976

23.0913485

0.00

18.410

33.500

52.800

109.500

▇▆▆▃▁

numeric

Hrs_RN_emp

0

1.0000000

35.8320679

23.2382688

0.00

18.320

33.380

52.600

109.500

▇▆▆▃▁

numeric

Hrs_RN_ctr

0

1.0000000

0.2003297

1.3107788

0.00

0.000

0.000

0.000

15.040

▇▁▁▁▁

numeric

Hrs_LPNadmin

0

1.0000000

5.3278621

8.6233057

0.00

0.000

0.000

8.150

34.250

▇▂▁▁▁

numeric

Hrs_LPNadmin_emp

0

1.0000000

5.3278621

8.6233057

0.00

0.000

0.000

8.150

34.250

▇▂▁▁▁

numeric

Hrs_LPNadmin_ctr

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_LPN

0

1.0000000

65.9722378

31.3701802

0.00

43.100

61.500

85.000

170.750

▂▇▅▂▁

numeric

Hrs_LPN_emp

0

1.0000000

63.5236863

32.9236849

0.00

37.530

58.420

84.500

170.750

▃▇▅▂▁

numeric

Hrs_LPN_ctr

0

1.0000000

2.4485514

6.2488032

0.00

0.000

0.000

0.000

37.570

▇▁▁▁▁

numeric

Hrs_CNA

0

1.0000000

158.4289810

72.1700250

27.25

103.500

132.260

203.000

362.750

▃▇▅▁▂

numeric

Hrs_CNA_emp

0

1.0000000

151.1220480

78.1015599

16.80

90.050

122.260

203.000

362.750

▅▇▆▂▂

numeric

Hrs_CNA_ctr

0

1.0000000

7.3069331

15.6678552

0.00

0.000

0.000

4.580

86.000

▇▁▁▁▁

numeric

Hrs_NAtrn

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_NAtrn_emp

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_NAtrn_ctr

0

1.0000000

0.0000000

0.0000000

0.00

0.000

0.000

0.000

0.000

▁▁▇▁▁

numeric

Hrs_MedAide

0

1.0000000

13.3417682

18.2443021

0.00

0.000

0.000

28.700

81.120

▇▂▂▁▁

numeric

Hrs_MedAide_emp

0

1.0000000

13.0389411

17.9741987

0.00

0.000

0.000

26.400

81.120

▇▂▂▁▁

numeric

Hrs_MedAide_ctr

0

1.0000000

0.3028272

1.6781050

0.00

0.000

0.000

0.000

26.130

▇▁▁▁▁

Data summary
Name Piped data
Number of rows 1638
Number of columns 29
_______________________
Column type frequency:
numeric 29
________________________
Group variables None

Variable type: numeric

Data summary
skim_variable complete_rate mean sd p0 p25 p50 p75 p100 hist
County_Fips 1.00 121.00 0.00 121.00 121.00 121.00 121.00 121.00 ▁▁▇▁▁
Density 0.89 840.76 260.60 177.00 956.40 956.40 956.40 956.40 ▁▁▁▁▇
WorkDate 1.00 20240215.68 83.03 20240101.00 20240123.00 20240215.00 20240309.00 20240331.00 ▇▁▇▁▇
MDScensus 1.00 124.60 59.13 21.00 86.00 106.00 172.00 276.00 ▂▇▂▃▁
Hrs_RNDON 1.00 5.43 4.08 0.00 0.00 8.00 8.00 16.50 ▅▁▇▁▁
Hrs_RNDON_emp 1.00 5.43 4.08 0.00 0.00 8.00 8.00 16.50 ▅▁▇▁▁
Hrs_RNDON_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_RNadmin 1.00 10.56 11.56 0.00 0.00 8.00 17.75 51.25 ▇▂▂▁▁
Hrs_RNadmin_emp 1.00 10.56 11.56 0.00 0.00 8.00 17.75 51.25 ▇▂▂▁▁
Hrs_RNadmin_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_RN_Density 0.89 0.04 0.05 0.00 0.01 0.03 0.05 0.32 ▇▁▁▁▁
Hrs_RN 1.00 25.92 21.55 0.00 11.00 20.50 36.30 114.43 ▇▅▂▁▁
Hrs_RN_emp 1.00 23.21 19.54 0.00 8.80 18.50 32.61 111.00 ▇▃▂▁▁
Hrs_RN_ctr 1.00 2.71 7.23 0.00 0.00 0.00 0.00 49.29 ▇▁▁▁▁
Hrs_LPNadmin 1.00 9.60 10.83 0.00 0.00 8.00 16.35 52.30 ▇▃▂▁▁
Hrs_LPNadmin_emp 1.00 9.58 10.84 0.00 0.00 8.00 16.35 52.30 ▇▃▂▁▁
Hrs_LPNadmin_ctr 1.00 0.03 0.48 0.00 0.00 0.00 0.00 8.00 ▇▁▁▁▁
Hrs_LPN 1.00 110.06 58.84 0.00 65.53 101.26 151.60 296.89 ▅▇▅▂▁
Hrs_LPN_emp 1.00 91.95 54.48 0.00 50.25 86.88 120.55 296.89 ▆▇▃▁▁
Hrs_LPN_ctr 1.00 18.12 26.90 0.00 0.00 0.00 25.50 123.43 ▇▁▁▁▁
Hrs_CNA 1.00 245.49 133.97 33.25 144.81 220.88 310.58 777.12 ▇▇▂▁▁
Hrs_CNA_emp 1.00 192.63 109.56 0.00 122.50 152.34 273.21 510.84 ▂▇▂▂▁
Hrs_CNA_ctr 1.00 52.86 77.03 0.00 0.00 0.00 86.19 319.54 ▇▁▁▁▁
Hrs_NAtrn 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_NAtrn_emp 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_NAtrn_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_MedAide 1.00 19.57 28.63 0.00 0.00 0.00 33.50 153.00 ▇▂▁▁▁
Hrs_MedAide_emp 1.00 19.57 28.63 0.00 0.00 0.00 33.50 153.00 ▇▂▁▁▁
Hrs_MedAide_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Name Piped data
Number of rows 1001
Number of columns 29
_______________________
Column type frequency:
numeric 29
________________________
Group variables None

Variable type: numeric

skim_variable complete_rate mean sd p0 p25 p50 p75 p100 hist
County_Fips 1.00 135.00 0.00 135.00 135.00 135.00 135.00 135.00 ▁▁▇▁▁
Density 0.91 469.47 217.14 29.00 345.80 465.75 640.20 830.70 ▂▇▁▇▂
WorkDate 1.00 20240215.68 83.05 20240101.00 20240123.00 20240215.00 20240309.00 20240331.00 ▇▁▇▁▇
MDScensus 1.00 86.30 37.28 28.00 59.00 90.00 109.00 164.00 ▅▆▇▃▂
Hrs_RNDON 1.00 5.89 4.25 0.00 0.00 8.00 8.00 19.80 ▅▁▇▁▁
Hrs_RNDON_emp 1.00 5.89 4.25 0.00 0.00 8.00 8.00 19.80 ▅▁▇▁▁
Hrs_RNDON_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_RNadmin 1.00 10.01 11.09 0.00 0.00 8.00 16.00 57.25 ▇▃▁▁▁
Hrs_RNadmin_emp 1.00 10.01 11.09 0.00 0.00 8.00 16.00 57.25 ▇▃▁▁▁
Hrs_RNadmin_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_RN_Density 0.91 0.24 0.56 0.00 0.05 0.08 0.12 2.97 ▇▁▁▁▁
Hrs_RN 1.00 36.03 23.09 0.00 18.41 33.50 52.80 109.50 ▇▆▆▃▁
Hrs_RN_emp 1.00 35.83 23.24 0.00 18.32 33.38 52.60 109.50 ▇▆▆▃▁
Hrs_RN_ctr 1.00 0.20 1.31 0.00 0.00 0.00 0.00 15.04 ▇▁▁▁▁
Hrs_LPNadmin 1.00 5.33 8.62 0.00 0.00 0.00 8.15 34.25 ▇▂▁▁▁
Hrs_LPNadmin_emp 1.00 5.33 8.62 0.00 0.00 0.00 8.15 34.25 ▇▂▁▁▁
Hrs_LPNadmin_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_LPN 1.00 65.97 31.37 0.00 43.10 61.50 85.00 170.75 ▂▇▅▂▁
Hrs_LPN_emp 1.00 63.52 32.92 0.00 37.53 58.42 84.50 170.75 ▃▇▅▂▁
Hrs_LPN_ctr 1.00 2.45 6.25 0.00 0.00 0.00 0.00 37.57 ▇▁▁▁▁
Hrs_CNA 1.00 158.43 72.17 27.25 103.50 132.26 203.00 362.75 ▃▇▅▁▂
Hrs_CNA_emp 1.00 151.12 78.10 16.80 90.05 122.26 203.00 362.75 ▅▇▆▂▂
Hrs_CNA_ctr 1.00 7.31 15.67 0.00 0.00 0.00 4.58 86.00 ▇▁▁▁▁
Hrs_NAtrn 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_NAtrn_emp 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_NAtrn_ctr 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ▁▁▇▁▁
Hrs_MedAide 1.00 13.34 18.24 0.00 0.00 0.00 28.70 81.12 ▇▂▂▁▁
Hrs_MedAide_emp 1.00 13.04 17.97 0.00 0.00 0.00 26.40 81.12 ▇▂▂▁▁
Hrs_MedAide_ctr 1.00 0.30 1.68 0.00 0.00 0.00 0.00 26.13 ▇▁▁▁▁

Hypothesis Testing

We ask if there is a statistical difference between the population averages of hours worked by Licensed Practical Nurses (LPN’s) between the states of Florida and Georgia. Using a two sided T-test with a significance factor of 5%, we observe that there is no difference in population averages, but there is a statistical difference in the variances. This suggests that there is a greater variability in the hours worked by LPN’s (see density and histogram plots for FL vs GA). We achieve similar results when comparing hours worked by Registered Nurses (RN’s) in Gwinnett and Fulton counties (from Georgia).

## [1] "There is no Statistical difference between the average hours worked by LPN's from GA and FL"
## [1] "There is a Statistical difference between the variances of hours worked by LPN's from GA and FL"
## [1] "There is a Statistical difference between the average hours worked by RN's in Gwinnett and Fulton Counties"
## [1] "There is a Statistical difference between the variances of hours worked by in Gwinnett and Fulton Counties"

We would like to visualize the previous results of our analysis. Let us recall, that the averages of hours worked for RN’s varies by states and counties. Not only is there a statistical significant difference between the average, but the shape of the distribution is quite distinct, which is apparent by looking at the PDF and CDF plots.

Interestingly, we observe that a decent proportion of Registered Nurses work more hours in Gwinnett county compared to Fulton county. We also observe Registered Nurses work more hours in the state of Florida compared to Georgia (on average) indicated by the CDF plot. Our results focus mainly on geography (states and counties), but there could be demographic factors of the population that affect the hours worked by employees.

Part 2

This section consists of SQL syntax embedded in R. Similar results can be obtained by using an SQL programming language, but is included here for simplicity.