Analysis Workshop: Who Holds the Door?

Part 1 — The Big Picture

This week you learned that people are less likely to help when other bystanders are present. In Darley and Latané's 1968 intercom study, 85% reported an apparent seizure when they believed they were the only listener and 31% when they believed four others could hear, and diffusion of responsibility is the main reason. Psychology only counts an everyday version of that claim as knowledge once it is measured. In this workshop you turn a small, everyday kind of helping into an operational definition, measure it at a public doorway, put one number on its link with how many people were nearby using the correlation coefficient r, and design the experiment that could test whether the number of bystanders causes a change. A chatbot then answers questions about your work, and you catch where it goes wrong.

Time budget: Plan for about 90 minutes.

Part 2 — The Task

Guiding question: At an ordinary doorway, is holding the door for the next person associated with how many other people are nearby, how would you measure that honestly, and what would it take to test whether the number of bystanders causes a change in helping?

Before you begin — hypothesis: Before you start watching, write one sentence in this form: If I watch 10 moments at a public doorway and count the other people nearby, then door-holding will ___ as more people are nearby because ___.

Workshop data: your-doorway-observation-run

Source: Your own tally of 10 everyday moments at a public doorway, recording how many other people were nearby and whether the person ahead held the door, collected in this workshop without names, photos, or recordings; no outside file is needed.

• Rows: 10 observed moments per run, one for each observation number from 1 to 10; the definition table has 5 rows, and the tally table has 11 rows, the 10 moments plus one row for r
• Columns: Observation number from 1 to 10, the count of other people nearby, and whether the door was held (1 for yes, 0 for no)

Part 3 — Materials & Procedure

Tools and materials

• Google Sheets (free) or Excel
• A notebook or phone notes app for tallies
• A document for your written answers

Ways of working

• operationalize-a-construct
• design-a-correlational-or-experimental-check
• compute-and-interpret-r

Procedure

1. Choose a busy public doorway where people come and go freely and watching is ordinary, such as a library, a campus building, or a store entrance. Fill in the first scaffold table, your operational definition, before you start: what counts as holding the door, what counts as nearby, and the rule for which moments you record. Do not take photos or videos, do not write down names or descriptions of anyone, and do not interfere with anyone. Tool: A notebook or phone notes app for tallies. Check: The first table is complete before you begin watching.
2. Watch for moments when one person goes through the door with another person a few steps behind. For each of the first 10 such moments, count the other people within about three steps of the door, not counting the two people involved, and write 1 if the person ahead held the door or 0 if they did not, in the second scaffold table. Tool: A notebook or phone notes app for tallies. Check: Ten rows, each with a count and a 1 or a 0. Plan on about 20 minutes of watching.
3. Open a blank sheet. Type Observation in cell A1, Others nearby in cell B1, and Held in cell C1, then type 1 through 10 in A2 through A11, your ten counts in B2 through B11, and your ten 1s and 0s in C2 through C11. Tool: Google Sheets (free) or Excel. Check: Column A runs 1, 2, 3, and so on up to 10.
4. In an empty cell, type =CORREL(B2:B11,C2:C11) and record the result to two decimals in the last row of the second table. If every door was held, or none was, or every count is the same, the formula shows an error because r cannot be computed when one variable never changes; record that and explain it in your first analysis answer. Tool: Google Sheets (free) or Excel. Check: A value between negative 1 and positive 1, or an error message if one column never changes.
5. Select B1 through C11 and insert a scatter chart with others nearby across the bottom and held up the side. Title both axes. Tool: Google Sheets (free) or Excel. Check: Ten dots, one per moment, that you can describe in words.
6. Fill in the third scaffold table, your experiment design, then answer the analysis questions and run the critique step in Part 6. Tool: A document for your written answers. Check: Three completed tables, five written answers, and a critique.

Fallback route

When to use it: Use this route if you cannot watch a public doorway, for example if no suitable place is available to you, or if a health, safety, or access reason makes observing in person unsuitable.

Write the operational definition in the first table for a doorway you know well, and describe in the second table the pattern you would predict for 10 moments rather than recording real ones. Then use the model data below in place of your own tally: compute r for the ten pairs with the same CORREL formula, make the scatter chart, and answer the first analysis question about these data. For questions 2 and 3, describe the pattern you would predict at a doorway and explain it with diffusion of responsibility. Complete the design table, the remaining questions, and the critique step. Submit the same items for equal credit.

This route earns the same credit as the primary route.

An illustrative paired dataset this course uses for practicing r, constructed for teaching rather than collected from real students.

Fallback model data

Hours of sleep	Quiz score (of 20)
5	11
6	14
6.5	12
7	15
7	13
7.5	16
8	17
8	14
8.5	18
9	17

Part 4 — The Scaffold

Write the operational definition first, because a construct you have not defined as a procedure is not yet measurable.

Student scaffold table 1

Part of the definition	Your entry
The doorway I watched, described by type only
What counts as holding the door
What counts as nearby	Within about three steps of the door, not counting the two people involved
Which moments I record	The first 10 moments when one person goes through with another person a few steps behind
What one 1 or 0 in the held column measures, in one sentence

Record each moment in order, because the count of others nearby and the held column are the two measured variables that r pairs.

Student scaffold table 2

Observation	Others nearby (count)	Held the door (1 = yes, 0 = no)
1
2
3
4
5
6
7
8
9
10
Correlation r (two decimals)

Plan the experiment that could test a cause, because your doorway tally can only show an association.

Student scaffold table 3

Design element	Your plan
The claim being tested	Having more bystanders present makes a person less likely to help someone who drops an armful of papers
Independent variable (IV) and its conditions
Dependent variable (DV) and how it is measured
How participants are assigned to conditions
How participants are chosen, and who the results could apply to
One third variable you would hold the same in every condition
What the result would be allowed to claim

Part 5 — Analysis Questions

1. Report your r to two decimals. Describe its direction and strength in words, and write one sentence that uses the phrase associated with. If r could not be computed, explain why in terms of your tallies.
2. Describe the pattern in your ten dots: were doors held more often when few people were nearby or when many were, which moment broke the pattern most, and do the dots suggest a clear trend or no clear trend?
3. Explain your result with this week's ideas. How would diffusion of responsibility predict the pattern, and why might holding a door, an everyday courtesy rather than an emergency, behave differently from reporting a seizure in Darley and Latané's study?
4. Your tally is correlational: you measured two variables but manipulated nothing. Name one third variable, such as how rushed people are at busy times, that could affect both the number of people nearby and door-holding, and explain how the experiment in your third table would rule out a third variable like that.
5. Choose one and answer it in 3–4 sentences. (a) If a friend tallied the same doorway beside you, would your 1s and 0s match? Say what that tells you about the reliability of your measure, and whether a reliable measure is automatically valid. (b) Could door-holding capture something other than helping, such as politeness, habit, or how heavy the door is? Explain the validity problem and suggest one change that would make the measure more valid.

Part 6 — AI-Critique Moment

Choose one equal-credit critique route. Route A: ask an approved AI tool to critique your completed work, then check its response against your own evidence. Route B is the no-AI equivalent printed below.

Approved tools: Claude, Gemini, ChatGPT, Grok, Microsoft Copilot.

Prompt to paste:

I watched a public doorway and recorded 10 moments when one person went through a door with someone else a few steps behind. For each moment I counted how many other people were nearby and whether the person ahead held the door (1 for yes, 0 for no). I've pasted my completed tables above, including my correlation r between people nearby and holding the door, and my plan for an experiment on group size and helping. Please answer five things in short sentences. First, does my correlation prove that having more people nearby causes people to help less? Second, in my planned experiment, which is the independent variable and which is the dependent variable? Third, if I want my results to apply to all adults in my city, should I use random assignment or random sampling? Fourth, a friend watched the same doorway with me and our tallies matched almost every time, so is door-holding a valid measure of helping? Fifth, is the idea that responsibility spreads thin across everyone present a theory or a hypothesis, and is my prediction that door-holding drops when more people are nearby a theory or a hypothesis?

Test the response for these likely failures:

• Chatbots often say a negative r proves that more people nearby makes each person less helpful, in the same way as Darley and Latané showed.
• Chatbots often call helping the independent variable because it is the main thing of interest, or call the number of people nearby an independent variable in the doorway tally.
• Chatbots often say random assignment to group sizes is what lets the results apply to all adults in the city.
• Chatbots often say that two observers agreeing on their tallies proves door-holding is a valid measure of helping.
• Chatbots often call the student's specific prediction a theory, or treat theory and hypothesis as the same thing.

Write 3–5 sentences naming one thing the chatbot got right and at least two places it went wrong or overreached, quoting its words and correcting each with evidence from your own tables or this week's course definitions.

Equivalent route (no AI required)

No AI account is required for this workshop. Instead of the chatbot, critique this flawed analysis, printed here in full: "Doors were held less often when more people were nearby, and my correlation was negative, which proves that crowds cause people to stop helping. In my experiment, whether the participant helps is the independent variable and the number of bystanders is the dependent variable. I will randomly assign people to the alone and crowded conditions so that my results apply to every adult in my city. My friend and I tallied the same doorway and matched almost every time, so door-holding is a valid measure of helping in emergencies. Diffusion of responsibility is only a hypothesis, while my prediction that door-holding drops in crowds is a theory." Mark it up: quote each flawed sentence, name what is wrong (cause read from a correlation, the IV and DV swapped, random assignment confused with random sampling, reliability confused with validity, or theory confused with hypothesis), cite the evidence from your tables or the course definitions, and write a corrected sentence beneath it. This route assesses the same objectives (Objective 8 and Objective 2) as the chatbot critique, takes comparable effort (about 30 minutes and 200–300 words), is scored by the same scoring criteria for the same credit, and its own submission artifact is the marked-up flawed analysis, posted in place of the chatbot share link and report.

Part 7 — What to Submit

• All three completed scaffold tables
• Your scatter chart with titled axes, or a labelled sketch of it
• Your hypothesis sentence and written answers to all five analysis questions
• The chatbot critique report with its share link, or the equivalent route's marked-up flawed analysis

Deliverable:

A short Analysis Workshop report: three completed tables (your operational definition of door-holding, your ten observed moments with r, and an experiment design), a scatter chart with titled axes or a labelled sketch, a hypothesis sentence and written answers to five analysis questions, and a critique of a chatbot's answers about your work, or, on the equivalent route, a marked-up correction of the printed flawed analysis. Submit in any accessible file type or as a link; a recorded response may be submitted as audio or video with a transcript, or as text. Choose a written, recorded, or visual form for your answers; every form is graded by the same scoring criteria.

Rubric

The rubric below shows how each submitted part is evaluated; bands are full, partial, or none.

Workshop evaluation criteria

Criterion	Full	Partial	None
Operational definition of door-holding and of nearby	The first table names the type of doorway, what counts as holding the door, what counts as nearby, the rule for which moments are recorded, and a one-sentence statement of what each 1 or 0 measures.	A definition is given, but what counts as holding, the nearby rule, the recording rule, or the one-sentence statement is missing or vague.	No operational definition is written.
Data, r, and its interpretation	Ten moments or the fallback data are recorded, r is computed and reported to two decimals or its error is explained, the scatter chart or sketch has titled axes, and the interpretation says associated with, gives direction and strength, and names a third variable.	The data and r are present, but the chart, the direction and strength, or the third variable is missing, or the sentence slips into cause.	No moments or correlation are recorded, or the values are invented.
Experimental design check	The design table puts the manipulated number of bystanders as the IV and the measured helping as the DV, uses random assignment for the conditions and random sampling for who could be studied, holds a third variable constant, and states what the result could claim.	The design is attempted, but the IV and DV are swapped, or assignment and sampling are confused, or the claim goes beyond the design.	No experiment design is submitted.
Bystander reasoning and the limitation	Questions 2 to 5 describe the pattern, explain it with diffusion of responsibility while noting how a courtesy differs from an emergency, connect the third variable to the experiment, and answer the chosen limitation question with an accurate account of reliability or validity.	Most questions are answered, but the doorway result is treated as proof of a cause, the courtesy-versus-emergency difference is ignored, reliability and validity are blurred, or a reason is missing.	The analysis questions are missing or do not address the measurement.
Critique of the chatbot or of the printed flawed analysis	On either route, at least two errors are quoted and corrected with evidence from the student's own tables or the course definitions, and one correct point is acknowledged; both routes earn this band equally.	On either route, errors are named but corrected without evidence, or only one error is caught.	No critique appears, or pasted output is submitted without any checking.

Quality Gate

• The operational definition is written before you start watching, and it names what counts as holding the door, what counts as nearby, and which moments you record.
• Every count, 1 or 0, and the correlation come from your own tally and formula, or from the fallback model data, never from memory or a chatbot.
• No names, photos, videos, or descriptions of any person appear anywhere in the submission, and no one was interfered with.
• The scatter chart puts others nearby across and held up, with both axes titled.
• Every sentence about r says associated with and names a third variable; no sentence claims the doorway tally shows that more people cause less helping.
• The design table names the IV, the DV, random assignment, and random sampling, each in its correct role.
• No statistic, tally, or source is invented anywhere in the submission.
• The critique quotes the chatbot or the flawed analysis and corrects at least two errors with evidence from your tables or the course definitions.