Week 1 — Quiz (auto-graded) · Statistics, Data & Study Design

Course: Introduction to Statistics (18-week generic edition)
Objective tested: Objective 1 — populations vs. samples; sampling & study design (plus levels of measurement).
Points: 10 (1 each) · Assignment group: Quizzes (15% of grade) · Due: end of Week 1 · Closed to AI.

This is the human-readable quiz with its vetted answer key and feedback. The import-ready Classic QTI is in F-quiz-week-01-qti.xml; the reusable item-bank entries and the Canvas placement block are at the bottom of this file.

Blueprint

No trick questions; distractors target the Week 1 misconceptions named in the lecture outline.

Questions, key, and feedback

Q1 (MC). An airline wants to know the average checked-bag weight for all 2.4 million passengers it flew last year. It weighs the bags of 1,500 randomly chosen passengers. What is the population?
- A. The 1,500 passengers whose bags were weighed
- B. The average weight of the 1,500 bags
- C. All 2.4 million passengers the airline flew last year ✅
- D. Passengers who checked more than one bag
Feedback: The population is everyone the question is about — all 2.4 million. The 1,500 are the sample. (Distractor A = the classic sample/population swap.)

Q2 (MC). Those 1,500 bags averaged 42.6 pounds. The value 42.6 pounds is a —
- A. Parameter
- B. Census
- C. Population
- D. Statistic ✅
Feedback: It was computed from the sample, so it's a statistic. The matching all-passenger figure would be a parameter. (P→P, S→S — the letters line up.)

Q3 (Multiple answer — select all that apply). Which of the following are quantitative variables?
- A. Daily high temperature in °F ✅
- B. A team's jersey color
- C. Number of pets in a household ✅
- D. Postal code
- E. Commute distance in miles ✅
Feedback: Quantitative = genuine amounts (temperature, counts, distance). Jersey color and postal code are categorical labels — a postal code is digits that name a place. (The numeric-looking label is the named trap.)

Q4 (MC). A restaurant records each order's spice level (mild / medium / hot / extra-hot). This variable is measured at the ordinal level because —
- A. The categories are pure name labels with no meaningful order at all
- B. The categories are ordered, but the gaps between them aren't equal or measurable ✅
- C. The categories are ordered with equal, measurable gaps and a true zero point
- D. The categories are written as numbers, so doing arithmetic on them is meaningful
Feedback: Ordered categories with fuzzy, unmeasurable gaps → ordinal. "Hot" beats "medium," but by no measurable amount.

Q5 (MC). Which variable is measured at the interval level?
- A. Number of siblings a student has
- B. The calendar year a car was manufactured ✅
- C. A city bus route number
- D. A household's weekly grocery bill
Feedback: Calendar years are ordered with equal gaps, but year zero is an arbitrary marker — not "no time" — so it's interval. Siblings and grocery bills are ratio (true zeros); a bus route number is a nominal label.

Q6 (Matching). Match each sampling method to its description.
| Method | Correct description |
|---|---|
| Simple random sample | Every individual — and every possible group of that size — is equally likely to be chosen |
| Stratified | Divide the population into meaningful groups, then draw a random sample within each group |
| Cluster | Randomly select whole groups and measure everyone inside the chosen groups |
| Systematic | Start at a random point in an ordered list and take every k-th individual |
Feedback: The classic mix-up: stratified samples within every group; cluster takes whole groups.

Q7 (MC). A city surveys residents about a park renovation by calling landline phone numbers on weekday afternoons. The biggest threat to this survey is —
- A. Undercoverage of residents without landlines or away from home on weekday afternoons ✅
- B. It is a complete census, so sampling problems cannot arise in the results
- C. Response bias caused by deliberately leading wording in the survey question
- D. Cluster sampling, because telephone exchanges group the city's residents naturally
Feedback: Whole slices of the population (younger residents, daytime workers, mobile-only households) never had a chance to be reached — that's undercoverage, bias baked into the frame.

Q8 (True / False). "A very large voluntary-response sample gives trustworthy results, because sheer size overcomes self-selection."
- True
- False ✅
Feedback: False. Self-selection is baked into the method; more opt-in responses are just more of the same lean. The 1936 Literary Digest poll had 2.4 million responses and still called the wrong winner. Method beats size.

Q9 (MC). A grocery chain analyzes its loyalty-card records and finds that shoppers who buy frozen vegetables also tend to buy more ice cream. Nothing was assigned; the chain only examined existing records. This study is —
- A. An experiment, because two groups of shoppers were compared
- B. An observational study, because no treatment was imposed on anyone ✅
- C. A census of all grocery shoppers in the region
- D. A stratified sample, because shoppers fall into natural groups
Feedback: Watching existing behavior without assigning anything = observational. Comparing groups doesn't make it an experiment — imposing a treatment does.

Q10 (MC). Across many cities, neighborhoods with more coffee shops have higher rents. The best conclusion is —
- A. Opening more coffee shops causes rents to rise
- B. Rising rents cause more coffee shops to open
- C. The two are associated, but a third variable could drive both ✅
- D. With enough neighborhoods measured, the link proves causation
Feedback: Observational data show a link, not an arrow; a confounder (overall economic activity and density) plausibly drives both. Correlation is a handshake, not a push.

Answer key (quick reference)

Quality gate (self-checked): each single-answer item has exactly one correct option; the multiple-answer item's three quantitative variables are the only quantitative options listed; no positional pattern in the key (C D · B B · A · B C) and no length giveaway (options within each item are comparable lengths); no item asserts a fact outside the Week 1 course definitions; no computation beyond reading a stated average, so no arithmetic to mis-key; no scenario reuses the tutorial, practice, chapter, lab, or assignment surfaces.

Item-bank entries (for variants + the midterm/final)

All ten items are tagged week=1 · objective=1 · topic=statistics-data-study-design and deposited in Item Bank: Week 1 — Statistics, Data & Study Design with idents w01q1–w01q10. The midterm (Week 9), the final (Week 18), and per-term variant updates draw fresh variants from this bank's concepts — never these live stems. (Tags: w01q1 population-sample, w01q2 parameter-statistic, w01q3 quantitative-categorical, w01q4 ordinal, w01q5 interval, w01q6 sampling-methods, w01q7 undercoverage, w01q8 size-vs-method, w01q9 study-design, w01q10 causation.)

Canvas placement block

canvas_object    = Quizzes::Quiz
title            = "Week 1 Quiz — Statistics, Data & Study Design"
assignment_group = "Quizzes"
points_possible  = 10
grading_type     = points
due_offset_days  = 6        # end of the module's week
published        = true
shuffle_answers  = true