In NUstat/ISDStutorials: Tutorial Lessons for Introduction to Statistics and Data Science

library(learnr)
library(tidyverse)
library(tutorialExtras)
library(gradethis)

gradethis_setup()
knitr::opts_chunk$set(echo = FALSE)

grade_server("grade")

question_text("Name:",
              answer_fn(function(value){
                              if(length(value) >= 1 ) {
                                return(mark_as(TRUE))
                                }
                              return(mark_as(FALSE) )
                              }),
              correct = "submitted",
              allow_retry = FALSE )

grade_button_ui(id = "grade")

Instructions

Complete this tutorial while reading Sections 9.2 - 9.4 of the textbook. Each question allows 3 'free' attempts. After the third attempt a 10% deduction occurs per attempt.

You can click the "View Grade" button as many times as you would like to see your current grade and the number of attempts you are on. Before submitting make sure your grade is as expected.

Goals

• Understand the theory of repeated sampling.
• Describe the properties of a sampling distribution.
• Understand the difference between a distribution and a sampling distribution.

Reading Quiz

quiz(
  caption = NULL,
  #Question 1
  question("Q1) Which of the following are TRUE about the theory of repeated samples? Select all that apply.  ",
           answer("It is a purely theoretical construct - you will not observe repeated samples in real life", correct = TRUE),
           answer("It allows us to calculate the true value of a population parameter exactly"),
           answer("It provides the theory for how we can use a sample to infer to a population", correct = TRUE),
           answer("It relies on the process of randomization (e.g. random sampling)", correct = TRUE),
           allow_retry = TRUE,
           random_answer_order = TRUE),
  # Question 2
  question_numeric("Q2) What is the maximum value of `replicate` in the `tactile_prop_red` dataset? ", 
           answer(33, correct = TRUE),
           allow_retry = TRUE),
  #Q3
  question_blank(paste0("<strong> Q3) </strong>  <br/>
  a) What does the value `TRUE` evaluate to in R? ___  <br/>
  b) What does the value `FALSE` evaluate to in R? ___"),
           answer("1", correct = TRUE),
           answer("0", correct = TRUE),
           allow_retry = TRUE),
  # Q4
  question_blank(paste0("<strong> Q4) Consider the tibble `coin_flips_RQ` shown below and the lines of code that follow. </strong>  <br/>",
  htmltools::img(src="images/coin_flips_RQ.png", height = 400, width = 200)," <br/>
`coin_flips_RQ %>%  
                summarize(
                  sum = sum(result),
                  mean = mean(result)
                  )`
                  <br/>
a) What is the resulting value for `sum`? ___ <br/>
b) What is the resulting value for `mean`? ___" ), 
           answer("3", correct = TRUE),
           answer_fn(function(value){
                if (value %in% c("0.3", ".3", "0.30")) {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           allow_retry = TRUE),
  # Q5
  question_blank(paste0("<strong> Q5) Consider the data frame `virtual_samples_RQ` that results from the following lines of code: </strong>  <br/>
           `virtual_samples_RQ <- bowl %>%  
                rep_sample_n(size = 50, reps = 5000)` <br/>

a) How many rows will `virtual_samples_RQ` have? ___ <br/>
b) What will be the maximum value of the `replicate` column? ___ <br/>
c) What will the value of `replicate` be for the 73rd row? ___ <br/>
d) How many rows will have `replicate == 437`? ___"),
           answer_fn(function(value){
                if (value %in% c("250000", "250,000")) {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           answer_fn(function(value){
                if (value %in% c("5000", "5,000")) {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           answer("2", correct = TRUE),
           answer("50", correct = TRUE),
           allow_retry = TRUE),
  # Q6
  question_blank("<strong> Q6) Consider the bowl of red and white balls in Figure 9.10 and its virtual analog in the data frame bowls. </strong>  <br/>
a) How many balls total are in the bowl? ___ <br/>
b) What is the true proportion of red balls in the bowl? ___ <br/>
c) How many red balls are in the bowl? ___ ",
           answer_fn(function(value){
                if (value %in% c("2400", "2,400")) {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           answer_fn(function(value){
                if (value %in% c("0.375", ".375")) {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           answer("900", correct = TRUE),
           allow_retry = TRUE),
  # Q7
  question("Q7) What phrase do we use to refer to the standard deviation of a sampling distribution? ", 
           type = "learnr_text",
           answer_fn(function(value){
                if (str_remove_all(str_to_lower(value), " ") == "standarderror") {
                    return(mark_as(TRUE))}
                    return(mark_as(FALSE) ) }),
           allow_retry = TRUE),
  # Q8
  question_wordbank("Q8) Match the following descriptions with the appropriate term:",
           choices = c("Standard deviation squared; a measure of spread in the data", "The difference between the average value of a sampling distribution and the true population parameter", "The distribution of possible values of estimates across repeated samples","A measure of spread of an estimator across repeated samples", "A parameter of the t-distribution that depends on sample size"),
           wordbank = c("Variance","Bias", "Sampling distribution", "Standard error", "Degrees of freedom"),
           answer(c("Variance","Bias", "Sampling distribution", "Standard error", "Degrees of freedom"), correct = TRUE),
           allow_retry = TRUE)
)

Submit

Once you are finished:

• Click the 'Download Grade' button below. This will download an html document of your grade summary.
• Make sure your grade is correct and as expected!
• Submit the downloaded html to Canvas.

grade_print_ui("grade")

NUstat/ISDStutorials documentation built on April 17, 2025, 6:15 p.m.