[Bug]:Tutorial 5, lesson 7. Problems with "Your Turn".

[mamcisaac]

Contact Details

mmcisaac@upei.ca

Bug

The "Your Turn" section of lesson 7 of Module 5 does not work. Two of the code blocks throw an "internal error", and the data set does not contain the variable that users are asked to consider:

Reproducible Example

Any attempt at using the code blocks at https://openintro.shinyapps.io/ims-05-infer-07/#section-your-turn-2 will reproduce this error.

As an aside, this "Reproducible Example" section of the new bug reporting template doesn't really make sense in the context of reporting bugs for these online tutorials.

Expected Behavior

acs12 contains information on hrs_work, not on hrly_pay, so most of the example needs to change. The first paragraph actually says the example will use "hrs_work", but the rest of example is about "hrly_pay" (which is not in the dataset):

Using the acs12 data, and specifically the variables income, hrs_work, and citizen, summarize, visualize, and compare the distributions of hourly pay rate for citizens and non-citizens.

Additionally, running the second or third code blocks results in "An internal error occurred while setting up the exercise. Please try again or contact the tutorial author."

Session Info

No response

Additional context

No response

[mamcisaac]

The t_test() code block that follows these throws the same error.

For now, I am having my students run all code in the first code block:

# Filter for non-missing hrs_work and non-missing citizen
acs12_complete_hrs_work_citizen <- acs12 |>
filter(!is.na(hrs_work), !is.na(citizen))


acs12_complete_hrs_work_citizen |>
# Group by citizen
group_by(citizen) |>
summarize(
# Calculate mean hours worked
mean_wage = mean(hrs_work),
# Calculate std dev of hours worked
s_wage = sd(hrs_work),
# Count number of rows
n_obs = n()
)


# Using acs12_complete_hrs_work_citizen, plot hrs_work
acs12_complete_hrs_work_citizen |>
ggplot(aes(x = hrs_work)) +
# Add a histogram layer
geom_histogram(binwidth = 5) +
facet_wrap(~citizen)


# Construct 90% CI using a t-test
test_results <- acs12_complete_hrs_work_citizen |>
t_test(hrs_work ~ citizen,
order = c("yes", "no"),
alternative = "two-sided",
conf_int = TRUE,
conf_level = 0.90)

# See the results
test_results