#Enter your getwd() code here
getwd()[1] "/Users/mayafrey/Desktop/MHC/Biostatistics/Biol234_Biostats/Lab 1"#Enter your setwd() code here
setwd("/Users/mayafrey/Desktop/MHC/Biostatistics/Biol234_Biostats/Lab 1/")Lab 1 Assignment
Complete ALL of the essentials below correctly to earn an ‘S’ on the lab.
Complete the Depth portion successful to earn credit toward a depth boost (every 2 lab depth assignments completed earns a 1/3 letter grade boost to your final grade)
Render your document as a .pdf or .html and submit it to the google folder on Moodle for grading.
Essentials
Open the document
1.) Opening this document confirms that you have a version of RStudio that is working! Try looking at the ‘visual’ tab to see what this document looks like when rendered and then render it and open the resulting file. This pipeline, which we call ‘render checking’ is really important! Render early, render often. When in doubt, render. Make sure your Quarto document is working after you make changes. /
Working directory
2.) Set the working directory Use getwd() to find the working directory. Then use setwd() and the GUI to set the working directory. Reminder: It is useful to have a folder for the course that you can use as your starting working directory when you load the RStudio Project for this class. Enter your getwd() and setwd() code in code chunk below
Reminder: To insert a code chunk into Quarto you can use ctrl+alt+I (windows) or cmd+alt+I (Mac) OR click ‘+C’ in the top bar.
Make a project
3.) Make an RStudio project for our class Name it whatever you’d like. I recommend “Biol234_Biostats” or something similar. Once it is done, take a screen shot of your RStudio screen and embed the image into below using the example code I have provided. It may also be helpful to make a folder on your server or computer for our class and use it as your working directory. /
Load packages
4.) Load packages without error. Load tidyverse (our favorite and most versatile package) and palmerpenguins (which is just fun data) in the code chunk below
#load packages
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0 ✔ purrr 1.0.1
✔ tibble 3.1.8 ✔ dplyr 1.0.10
✔ tidyr 1.3.0 ✔ stringr 1.5.0
✔ readr 2.1.3 ✔ forcats 0.5.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()library(palmerpenguins)Data Viewing
5.) Basic data viewing - use the dataset mtcars as I did in the lab explanation. Use head(), tail(), str(), nrow(), ncol(), and then change a column from a number to a factor and from a factor back to a number. Confirm that each one of these actions works! Insert a code chunk below to begin
mtcars2 <- mtcars
#Shows first 6 rows of data
head(mtcars2) mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1#Shows last 6 rows of data
tail(mtcars2) mpg cyl disp hp drat wt qsec vs am gear carb
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.7 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.9 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.5 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.5 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.6 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.6 1 1 4 2#Shows attributes of each column
str(mtcars2)'data.frame': 32 obs. of 11 variables:
$ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
$ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
$ disp: num 160 160 108 258 360 ...
$ hp : num 110 110 93 110 175 105 245 62 95 123 ...
$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
$ wt : num 2.62 2.88 2.32 3.21 3.44 ...
$ qsec: num 16.5 17 18.6 19.4 17 ...
$ vs : num 0 0 1 1 0 1 0 1 1 1 ...
$ am : num 1 1 1 0 0 0 0 0 0 0 ...
$ gear: num 4 4 4 3 3 3 3 4 4 4 ...
$ carb: num 4 4 1 1 2 1 4 2 2 4 ...#Shows number of rows
nrow(mtcars2)[1] 32#Shows number of columns
ncol(mtcars2)[1] 11#Change column from number to factor
mtcars2$mpg = as.factor(mtcars2$mpg)
str(mtcars2)'data.frame': 32 obs. of 11 variables:
$ mpg : Factor w/ 25 levels "10.4","13.3",..: 16 16 19 17 13 12 3 20 19 14 ...
$ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
$ disp: num 160 160 108 258 360 ...
$ hp : num 110 110 93 110 175 105 245 62 95 123 ...
$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
$ wt : num 2.62 2.88 2.32 3.21 3.44 ...
$ qsec: num 16.5 17 18.6 19.4 17 ...
$ vs : num 0 0 1 1 0 1 0 1 1 1 ...
$ am : num 1 1 1 0 0 0 0 0 0 0 ...
$ gear: num 4 4 4 3 3 3 3 4 4 4 ...
$ carb: num 4 4 1 1 2 1 4 2 2 4 ...#Change column back to number from factor
mtcars2$mpg = as.numeric(as.character((mtcars2$mpg)))
str(mtcars2)'data.frame': 32 obs. of 11 variables:
$ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
$ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
$ disp: num 160 160 108 258 360 ...
$ hp : num 110 110 93 110 175 105 245 62 95 123 ...
$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
$ wt : num 2.62 2.88 2.32 3.21 3.44 ...
$ qsec: num 16.5 17 18.6 19.4 17 ...
$ vs : num 0 0 1 1 0 1 0 1 1 1 ...
$ am : num 1 1 1 0 0 0 0 0 0 0 ...
$ gear: num 4 4 4 3 3 3 3 4 4 4 ...
$ carb: num 4 4 1 1 2 1 4 2 2 4 ...Depth
Make a directory and folders
1.) Make a directory (folder) for our class, set it as the wd for your project and then add the following folders within the directory: data, code, labs. Screenshot this folder and insert the image into your Quarto report below
Penguins Data Viewing
2.) Do basic data viewing on the penguins dataset from the palmerpenguins package. This includes head(), tail(), str(), nrow(), ncol(), and changing column attributes (as in Essentials #5). CONFIRM that all work! Insert a code chunk below to begin
penguins2 <- penguins_raw
#Shows first 6 rows
head(penguins2)# A tibble: 6 × 17
study…¹ Sampl…² Species Region Island Stage Indiv…³ Clutc…⁴ `Date Egg` Culme…⁵
<chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <date> <dbl>
1 PAL0708 1 Adelie… Anvers Torge… Adul… N1A1 Yes 2007-11-11 39.1
2 PAL0708 2 Adelie… Anvers Torge… Adul… N1A2 Yes 2007-11-11 39.5
3 PAL0708 3 Adelie… Anvers Torge… Adul… N2A1 Yes 2007-11-16 40.3
4 PAL0708 4 Adelie… Anvers Torge… Adul… N2A2 Yes 2007-11-16 NA
5 PAL0708 5 Adelie… Anvers Torge… Adul… N3A1 Yes 2007-11-16 36.7
6 PAL0708 6 Adelie… Anvers Torge… Adul… N3A2 Yes 2007-11-16 39.3
# … with 7 more variables: `Culmen Depth (mm)` <dbl>,
# `Flipper Length (mm)` <dbl>, `Body Mass (g)` <dbl>, Sex <chr>,
# `Delta 15 N (o/oo)` <dbl>, `Delta 13 C (o/oo)` <dbl>, Comments <chr>, and
# abbreviated variable names ¹studyName, ²`Sample Number`, ³`Individual ID`,
# ⁴`Clutch Completion`, ⁵`Culmen Length (mm)`#Shows last 6 rows
tail(penguins2)# A tibble: 6 × 17
study…¹ Sampl…² Species Region Island Stage Indiv…³ Clutc…⁴ `Date Egg` Culme…⁵
<chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <date> <dbl>
1 PAL0910 63 Chinst… Anvers Dream Adul… N98A1 Yes 2009-11-19 45.7
2 PAL0910 64 Chinst… Anvers Dream Adul… N98A2 Yes 2009-11-19 55.8
3 PAL0910 65 Chinst… Anvers Dream Adul… N99A1 No 2009-11-21 43.5
4 PAL0910 66 Chinst… Anvers Dream Adul… N99A2 No 2009-11-21 49.6
5 PAL0910 67 Chinst… Anvers Dream Adul… N100A1 Yes 2009-11-21 50.8
6 PAL0910 68 Chinst… Anvers Dream Adul… N100A2 Yes 2009-11-21 50.2
# … with 7 more variables: `Culmen Depth (mm)` <dbl>,
# `Flipper Length (mm)` <dbl>, `Body Mass (g)` <dbl>, Sex <chr>,
# `Delta 15 N (o/oo)` <dbl>, `Delta 13 C (o/oo)` <dbl>, Comments <chr>, and
# abbreviated variable names ¹studyName, ²`Sample Number`, ³`Individual ID`,
# ⁴`Clutch Completion`, ⁵`Culmen Length (mm)`#Shows attributes of columns
str(penguins2)tibble [344 × 17] (S3: tbl_df/tbl/data.frame)
$ studyName : chr [1:344] "PAL0708" "PAL0708" "PAL0708" "PAL0708" ...
$ Sample Number : num [1:344] 1 2 3 4 5 6 7 8 9 10 ...
$ Species : chr [1:344] "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" ...
$ Region : chr [1:344] "Anvers" "Anvers" "Anvers" "Anvers" ...
$ Island : chr [1:344] "Torgersen" "Torgersen" "Torgersen" "Torgersen" ...
$ Stage : chr [1:344] "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" ...
$ Individual ID : chr [1:344] "N1A1" "N1A2" "N2A1" "N2A2" ...
$ Clutch Completion : chr [1:344] "Yes" "Yes" "Yes" "Yes" ...
$ Date Egg : Date[1:344], format: "2007-11-11" "2007-11-11" ...
$ Culmen Length (mm) : num [1:344] 39.1 39.5 40.3 NA 36.7 39.3 38.9 39.2 34.1 42 ...
$ Culmen Depth (mm) : num [1:344] 18.7 17.4 18 NA 19.3 20.6 17.8 19.6 18.1 20.2 ...
$ Flipper Length (mm): num [1:344] 181 186 195 NA 193 190 181 195 193 190 ...
$ Body Mass (g) : num [1:344] 3750 3800 3250 NA 3450 ...
$ Sex : chr [1:344] "MALE" "FEMALE" "FEMALE" NA ...
$ Delta 15 N (o/oo) : num [1:344] NA 8.95 8.37 NA 8.77 ...
$ Delta 13 C (o/oo) : num [1:344] NA -24.7 -25.3 NA -25.3 ...
$ Comments : chr [1:344] "Not enough blood for isotopes." NA NA "Adult not sampled." ...
- attr(*, "spec")=
.. cols(
.. studyName = col_character(),
.. `Sample Number` = col_double(),
.. Species = col_character(),
.. Region = col_character(),
.. Island = col_character(),
.. Stage = col_character(),
.. `Individual ID` = col_character(),
.. `Clutch Completion` = col_character(),
.. `Date Egg` = col_date(format = ""),
.. `Culmen Length (mm)` = col_double(),
.. `Culmen Depth (mm)` = col_double(),
.. `Flipper Length (mm)` = col_double(),
.. `Body Mass (g)` = col_double(),
.. Sex = col_character(),
.. `Delta 15 N (o/oo)` = col_double(),
.. `Delta 13 C (o/oo)` = col_double(),
.. Comments = col_character()
.. )#Shows number of rows
nrow(penguins2)[1] 344#Shows number of columns
ncol(penguins2)[1] 17#Change column from number to factor
penguins2$`Body Mass (g)` <- as.factor(penguins2$`Body Mass (g)`)
str(penguins2)tibble [344 × 17] (S3: tbl_df/tbl/data.frame)
$ studyName : chr [1:344] "PAL0708" "PAL0708" "PAL0708" "PAL0708" ...
$ Sample Number : num [1:344] 1 2 3 4 5 6 7 8 9 10 ...
$ Species : chr [1:344] "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" ...
$ Region : chr [1:344] "Anvers" "Anvers" "Anvers" "Anvers" ...
$ Island : chr [1:344] "Torgersen" "Torgersen" "Torgersen" "Torgersen" ...
$ Stage : chr [1:344] "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" ...
$ Individual ID : chr [1:344] "N1A1" "N1A2" "N2A1" "N2A2" ...
$ Clutch Completion : chr [1:344] "Yes" "Yes" "Yes" "Yes" ...
$ Date Egg : Date[1:344], format: "2007-11-11" "2007-11-11" ...
$ Culmen Length (mm) : num [1:344] 39.1 39.5 40.3 NA 36.7 39.3 38.9 39.2 34.1 42 ...
$ Culmen Depth (mm) : num [1:344] 18.7 17.4 18 NA 19.3 20.6 17.8 19.6 18.1 20.2 ...
$ Flipper Length (mm): num [1:344] 181 186 195 NA 193 190 181 195 193 190 ...
$ Body Mass (g) : Factor w/ 94 levels "2700","2850",..: 32 34 13 NA 20 28 27 61 21 47 ...
$ Sex : chr [1:344] "MALE" "FEMALE" "FEMALE" NA ...
$ Delta 15 N (o/oo) : num [1:344] NA 8.95 8.37 NA 8.77 ...
$ Delta 13 C (o/oo) : num [1:344] NA -24.7 -25.3 NA -25.3 ...
$ Comments : chr [1:344] "Not enough blood for isotopes." NA NA "Adult not sampled." ...
- attr(*, "spec")=
.. cols(
.. studyName = col_character(),
.. `Sample Number` = col_double(),
.. Species = col_character(),
.. Region = col_character(),
.. Island = col_character(),
.. Stage = col_character(),
.. `Individual ID` = col_character(),
.. `Clutch Completion` = col_character(),
.. `Date Egg` = col_date(format = ""),
.. `Culmen Length (mm)` = col_double(),
.. `Culmen Depth (mm)` = col_double(),
.. `Flipper Length (mm)` = col_double(),
.. `Body Mass (g)` = col_double(),
.. Sex = col_character(),
.. `Delta 15 N (o/oo)` = col_double(),
.. `Delta 13 C (o/oo)` = col_double(),
.. Comments = col_character()
.. )#Change column back to factor from number
penguins2$`Body Mass (g)` <- as.numeric(as.character(penguins2$`Body Mass (g)`))
str(penguins2)tibble [344 × 17] (S3: tbl_df/tbl/data.frame)
$ studyName : chr [1:344] "PAL0708" "PAL0708" "PAL0708" "PAL0708" ...
$ Sample Number : num [1:344] 1 2 3 4 5 6 7 8 9 10 ...
$ Species : chr [1:344] "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" "Adelie Penguin (Pygoscelis adeliae)" ...
$ Region : chr [1:344] "Anvers" "Anvers" "Anvers" "Anvers" ...
$ Island : chr [1:344] "Torgersen" "Torgersen" "Torgersen" "Torgersen" ...
$ Stage : chr [1:344] "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" "Adult, 1 Egg Stage" ...
$ Individual ID : chr [1:344] "N1A1" "N1A2" "N2A1" "N2A2" ...
$ Clutch Completion : chr [1:344] "Yes" "Yes" "Yes" "Yes" ...
$ Date Egg : Date[1:344], format: "2007-11-11" "2007-11-11" ...
$ Culmen Length (mm) : num [1:344] 39.1 39.5 40.3 NA 36.7 39.3 38.9 39.2 34.1 42 ...
$ Culmen Depth (mm) : num [1:344] 18.7 17.4 18 NA 19.3 20.6 17.8 19.6 18.1 20.2 ...
$ Flipper Length (mm): num [1:344] 181 186 195 NA 193 190 181 195 193 190 ...
$ Body Mass (g) : num [1:344] 3750 3800 3250 NA 3450 ...
$ Sex : chr [1:344] "MALE" "FEMALE" "FEMALE" NA ...
$ Delta 15 N (o/oo) : num [1:344] NA 8.95 8.37 NA 8.77 ...
$ Delta 13 C (o/oo) : num [1:344] NA -24.7 -25.3 NA -25.3 ...
$ Comments : chr [1:344] "Not enough blood for isotopes." NA NA "Adult not sampled." ...
- attr(*, "spec")=
.. cols(
.. studyName = col_character(),
.. `Sample Number` = col_double(),
.. Species = col_character(),
.. Region = col_character(),
.. Island = col_character(),
.. Stage = col_character(),
.. `Individual ID` = col_character(),
.. `Clutch Completion` = col_character(),
.. `Date Egg` = col_date(format = ""),
.. `Culmen Length (mm)` = col_double(),
.. `Culmen Depth (mm)` = col_double(),
.. `Flipper Length (mm)` = col_double(),
.. `Body Mass (g)` = col_double(),
.. Sex = col_character(),
.. `Delta 15 N (o/oo)` = col_double(),
.. `Delta 13 C (o/oo)` = col_double(),
.. Comments = col_character()
.. )Reformatting document
3.) Reformat this document to add headers (heading level1 and2 at least!), change formatting of text in other ways. Make at least 3 types of change and document them below (you canjust type out text of what you did). The formatting changes should show up as visual differences in your final report!
When you are done, you can turn in your assignment on Moodle (using the google form)
- I added additional headers (heading level 2) to the Essentials and Depth sections
- I italicized the instructions for this part
- I added superscript to the instructions for this part