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Computer Science
Date
Feb 20, 2024
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9
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1/30/24, 1:09 AM
lab 1.2
https://stat20.datahub.berkeley.edu/user/aisharakyan/rstudio/p/2f2e0a1b/
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── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.1.3 ✔ readr 2.1.4
✔ forcats 1.0.0 ✔ stringr 1.5.0
✔ ggplot2 3.4.4 ✔ tibble 3.2.1
✔ lubridate 1.9.3 ✔ tidyr 1.3.0
✔ purrr 1.0.2 ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ
Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
library
(stat20data)
library
(tidyverse)
data
(class_survey)
ggplot
(
data=
class_survey,
mapping = aes
(
x = coding_exp_scale)) +
geom_histogram
()
1/30/24, 1:09 AM
lab 1.2
https://stat20.datahub.berkeley.edu/user/aisharakyan/rstudio/p/2f2e0a1b/
2/9
# A tibble: 619 × 1
coding_exp_scale
<dbl>
1 1
2 1
3 7
4 6
5 2
6 5
7 4
8 8
9 1
10 5
# ℹ
609 more rows
library
(tidyverse)
library
(dplyr)
coding_experience <- select
(class_survey, coding_exp_scale)
coding_experience
1/30/24, 1:09 AM
lab 1.2
https://stat20.datahub.berkeley.edu/user/aisharakyan/rstudio/p/2f2e0a1b/
3/9
# A tibble: 1 × 2
coding_experience_IQR coding_experience_median
<dbl> <dbl>
1 4 2
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
summarise
(coding_experience,
coding_experience_IQR = IQR
(coding_exp_scale),
coding_experience_median = median
(coding_exp_scale))
library
(stat20data)
library
(tidyverse)
library
(ggplot2)
data
(class_survey)
filtered_survey <- filter
(class_survey, new_COVID_variant >= 0
,
new_COVID_variant < 1
)
ggplot
(
data = filtered_survey, mapping = aes
(
x= new_COVID_variant)) +
geom_histogram
()
1/30/24, 1:09 AM
lab 1.2
https://stat20.datahub.berkeley.edu/user/aisharakyan/rstudio/p/2f2e0a1b/
4/9
# A tibble: 1 × 1
filtered_survey_sd
<dbl>
1 0.222
library
(stat20data)
data
(class_survey)
filtered_survey <- filter
(class_survey,
new_COVID_variant >= 0
,
new_COVID_variant < 1
)
summarise
(filtered_survey,
filtered_survey_sd = sd
(new_COVID_variant))
library
(stat20data)
data
(class_survey)
filtered_survey <- filter
(class_survey,
new_COVID_variant >= 0
,
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WIND
20PSF
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