HW3_IanKennedy

HW3 for DACSS 601.

For my final project I’ll be using a data set from the Research Lab (FFRC) I’ve been working with for the past few years. In short, the FFRC, in coordination with the USDA Forest Service, implements an annual survey (TPO) which attempts to track timber procurement and lumber production at mills throughout the USA. Below, I’ve selected the columns of interest, of which there are 5. MILL_NBR (numeric), MILL_STATECD (numeric), MILL_NAME (string), and MILL_STATUS_CD (numeric) are all included for identification purposes. TOT_MCF (numeric) is the column of interest, as I’ll be looking to gauge the breadth of mills included in our survey efforts. Specifically, I’ll be running analyses to see how shifting the baseline for minimum volume procured (TOT_MCF) would impact the number of mills and total volume of procured timber included in the sample frame. I’ve also added a new column (Volume_Code) which will be updated based on the volume that is landed on. Generally speaking, this sort of analysis will attempt to answer the following research questions:

1. Does it make sense to exclude small-production/hobby mills from future survey attempts?
2. If yes, what is the minimum volume (TOT_MCF) that mills should have procured to be included in survey efforts?
3. What impact would shifting the baseline (regardless of minimum volume utilized) have on the total volume and number of mills that are surveyed?

There will likely be further questions that will need to be analyzed, however these questions outline the main priorities of data analysis for this project.

HW3_Data <- read_excel(path = "C:/Users/kenne/Documents/R_Workspace/TPO_Sample.xlsx")
HW3_Data %>%
  select(MILL_NBR, MILL_STATECD, MILL_NAME, MILL_STATUS_CD, TOT_MCF)%>%
  arrange(TOT_MCF)%>%
  mutate(Volume_Code = case_when(TOT_MCF > 1.6666667 ~ 2, 
                                 TOT_MCF <= 1.6666667 ~ 1))%>%
  arrange(Volume_Code)%>%

  head()

# A tibble: 6 x 6
  MILL_NBR   MILL_STATECD MILL_NAME MILL_STATUS_CD TOT_MCF Volume_Code
  <chr>             <dbl> <chr>              <dbl>   <dbl>       <dbl>
1 3005                 55 NEWPAGE ~             NA 0                 1
2 5                    34 ON-SITE ~              2 0.00953           1
3 902                  26 FARMER B~              2 0.0172            1
4 344                  27 PRAIRIE ~              2 0.02              1
5 N/A - Nev~           18 ROGER BR~              3 0.0316            1
6 731                  26 PINE RID~              2 0.0316            1