Type: | Package |
Title: | Experience Research |
Version: | 0.1.1 |
Description: | Provides convenience functions for researching experiences including user, customer, patient, employee, and other human experiences. It provides a suite of tools to simplify data exploration such as benchmarking, comparing groups, and checking for differences. The outputs translate statistical approaches in applied experience research to human readable output. |
License: | MIT + file LICENSE |
Encoding: | UTF-8 |
Imports: | cli, dplyr, huxtable, magrittr, scales, stringr, tibble |
RoxygenNote: | 7.2.1 |
NeedsCompilation: | no |
Packaged: | 2022-10-29 14:09:25 UTC; Home |
Author: | Joe Chelladurai |
Maintainer: | Joe Chelladurai <joe.chelladurai@outlook.com> |
Repository: | CRAN |
Date/Publication: | 2022-10-31 14:10:12 UTC |
experiences: Experience Research
Description
Provides convenience functions for researching experiences. The functions are designed to translate statistical approaches to applied experience research.
Author(s)
Maintainer: Joe Chelladurai joe.chelladurai@outlook.com (ORCID)
Compare Probability of an Event with Benchmark
Description
Compare Probability of an Event with Benchmark
Usage
compare_benchmark_event(
benchmark,
event,
total,
event_type = "",
notes = c("minimal", "technical")
)
Arguments
benchmark |
benchmark |
event |
event |
total |
total |
event_type |
Optional: a string describing the type of event. For example, success, failure, etc. |
notes |
whether output should contain minimal, technical, or executive type of notes. |
Value
list of event rate, probability, notes
Examples
compare_benchmark_event(benchmark = 0.7,
event = 10,
total = 12,
event_type = "success",
notes = "minimal")
Compare Score with a Benchmark
Description
Compare Score with a Benchmark
Usage
compare_benchmark_score(
data,
benchmark,
alpha,
tail = "one",
remove_missing = TRUE
)
Arguments
data |
a column or vector of scores |
benchmark |
benchmark |
alpha |
alpha |
tail |
one-tailed or two-tailed test |
remove_missing |
TRUE/FALSE remove missing values? (default is TRUE) |
Value
lower_ci, upper_ci, t, probability
Examples
data <- 68 + 17 * scale(rnorm(20)) # 68 = mean, 17 = sd
compare_benchmark_score(data, benchmark = 60, alpha = 0.5)
Compare Time with a Benchmark
Description
Compare Time with a Benchmark
Usage
compare_benchmark_time(benchmark, time, alpha, remove_missing = FALSE)
Arguments
benchmark |
benchmark |
time |
a column or vector of time values |
alpha |
alpha |
remove_missing |
TRUE/FALSE remove missing values? |
Value
lower_ci, upper_ci, t, probability
Examples
compare_benchmark_time(time = c(60, 53, 70, 42, 62, 43, 81),
benchmark = 60,
alpha = 0.05)
T distribution - one-tailed
Description
T distribution - one-tailed
Usage
t_dist_one_tailed(t_score, degrees_of_freedom)
Arguments
t_score |
t value |
degrees_of_freedom |
degrees of freedom |
Value
value
T distribution - two-tailed
Description
T distribution - two-tailed
Usage
t_dist_two_tailed(t_score, degrees_of_freedom)
Arguments
t_score |
t value |
degrees_of_freedom |
degrees of freedom |
Value
value