Create two objects in your environment, x and y. Assign x as a vector of numbers 1, 2, and 3. Assign y as a vector of numbers 4, 5, and 6. Once complete, check that both objects are visible in your RStudio environment.
x <- c(1, 2, 3)
y <- c(4, 5, 6)
x## [1] 1 2 3y## [1] 4 5 6Clear your environment. Check that x and y are no longer in the environment by typing each letter in the console. What is the result?
rm(list = ls())Check your R session info. Which version of R are you running? Which version of the knitr package are you running? Write these details below.
sessionInfo()## R version 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] esquisse_2.0.0 ThemePark_0.0.1 readxl_1.4.3 naniar_1.1.0
## [5] jhur_0.2.1 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1
## [9] dplyr_1.1.4 purrr_1.0.2 tidyr_1.3.1 tibble_3.2.1
## [13] ggplot2_3.5.1 tidyverse_2.0.0 readr_2.1.5
##
## loaded via a namespace (and not attached):
## [1] writexl_1.5.0 tidyselect_1.2.1 farver_2.1.2
## [4] fastmap_1.2.0 promises_1.3.0 digest_0.6.36
## [7] timechange_0.3.0 toastui_0.3.3 mime_0.12
## [10] lifecycle_1.0.4 magrittr_2.0.3 compiler_4.4.1
## [13] rlang_1.1.4 sass_0.4.9 tools_4.4.1
## [16] utf8_1.2.4 yaml_2.3.9 data.table_1.15.4
## [19] knitr_1.48 labeling_0.4.3 htmlwidgets_1.6.4
## [22] bit_4.0.5 classInt_0.4-10 curl_5.2.1
## [25] shinybusy_0.3.3 showtextdb_3.0 KernSmooth_2.23-24
## [28] withr_3.0.0 shinyWidgets_0.8.6 grid_4.4.1
## [31] fansi_1.0.6 sysfonts_0.8.9 xtable_1.8-4
## [34] e1071_1.7-14 colorspace_2.1-0 scales_1.3.0
## [37] optparse_1.7.5 cli_3.6.3 rmarkdown_2.27
## [40] crayon_1.5.3 ragg_1.3.2 datamods_1.5.1
## [43] generics_0.1.3 rstudioapi_0.16.0 tzdb_0.4.0
## [46] getopt_1.20.4 cachem_1.1.0 proxy_0.4-27
## [49] parallel_4.4.1 cellranger_1.1.0 vctrs_0.6.5
## [52] jsonlite_1.8.8 hms_1.1.3 bit64_4.0.5
## [55] visdat_0.6.0 systemfonts_1.1.0 jquerylib_0.1.4
## [58] rio_1.1.1 glue_1.7.0 stringi_1.8.4
## [61] gtable_0.3.5 later_1.3.2 munsell_0.5.1
## [64] pillar_1.9.0 htmltools_0.5.8.1 showtext_0.9-7
## [67] reactable_0.4.4 R6_2.5.1 textshaping_0.4.0
## [70] vroom_1.6.5 evaluate_0.24.0 shiny_1.8.1.1
## [73] highr_0.11 httpuv_1.6.15 bslib_0.7.0
## [76] phosphoricons_0.2.1 class_7.3-22 Rcpp_1.0.12
## [79] xfun_0.45 pkgconfig_2.0.3knitr version:Create a vector z with the numbers 0 to 9. Set the seed for the R random number generator to 1234. Draw 5 numbers at random from z using the sample() function with replace = TRUE. Repeatedly run the code 3 times and note what you observe.
z <- 0:9
set.seed(1234)
sample(x = z, size = 5, replace = TRUE)## [1] 9 5 4 8 4Run the sample() statement again, but this time without running the set.seed() line. What do you notice about the 5 numbers?
sample(x = z, size = 5, replace = TRUE)## [1] 5 3 1 6 5