Week 2 Data Lab: Picture the Penguins

Part 1 — The Big Picture

This week you learned that a long list of values becomes readable as a table and a picture, and that a picture can tell the truth or bend it. In this lab you open the real penguin field log yourself, count the species and turn the counts into shares, draw a bar chart and a histogram, read the shape of the body masses by their tail, and fill a two-way table of species by island. Then you crop a chart's axis on purpose to see how a picture can mislead, and you check a chatbot's description of the same data.

Time budget: Plan for about 90 minutes.

Part 2 — The Task

Guiding question: What do the species counts and the body masses in the penguin field log look like, and which picture shows each one honestly?

Workshop data: palmer-station-penguins

Get the data: palmer-station-penguins landing page or the direct data file — free, no login required.

Source: Measurements of 344 penguins of three species on three islands of Antarctica's Palmer Archipelago, recorded by field researchers and republished in the palmerpenguins package.

• Rows: 344 penguins
• Columns: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, sex, year
• Missing values: Numeric measurement columns and sex carry missing values for a small number of penguins

Part 3 — Materials & Procedure

Tools and materials

• Google Sheets (free) or Excel
• The palmerpenguins CSV file
• A document or notebook for your written answers

Ways of working

• interpret-real-data
• compute-and-plot
• structured-observation

Procedure

1. Open a blank sheet. In Google Sheets, click cell A1 and type =IMPORTDATA("https://raw.githubusercontent.com/allisonhorst/palmerpenguins/main/inst/extdata/penguins.csv"). In Excel, save the file from that address, then use Data, then From Text/CSV, and load it starting in cell A1. Tool: Google Sheets (free) or Excel. Check: Row 1 shows the eight column names, and the penguins fill rows 2 through 345.
2. In three empty cells, count each species with =COUNTIF(A2:A345,"Adelie"), then the same for Chinstrap and Gentoo. Beside each count, divide by 344 to get its share, for example =COUNTIF(A2:A345,"Adelie")/344, and format the share as a percent with one decimal. Record the counts and shares in the first scaffold table. Tool: Google Sheets (free) or Excel. Check: The three counts add to 344, and the three shares add to 100.0%.
3. Select your small table of species and counts. Use Insert, then Chart, and choose Column chart in Google Sheets or the Column chart button in Excel. Make sure the vertical axis starts at 0. Tool: Google Sheets (free) or Excel. Check: Three separate bars with gaps between them; the Adelie bar is the tallest and the Chinstrap bar the shortest.
4. Select F1:F345, the body_mass_g column. In Google Sheets use Insert, then Chart, set Chart type to Histogram chart, and under Customize, then Histogram, set Bucket size to 500. In Excel use Insert, then Insert Statistic Chart, then Histogram, and set Bin width to 500 under Format Axis. Then, in empty cells, type =COUNT(F2:F345), =MIN(F2:F345), =MAX(F2:F345), =MEDIAN(F2:F345), and =AVERAGE(F2:F345), and record them in the second scaffold table. Tool: Google Sheets (free) or Excel. Check: Touching bars run from 2,500 g to 6,500 g; the count of masses is 342, the lightest is 2,700 g, and the heaviest is 6,300 g.
5. Fill the two-way table of species by island with =COUNTIFS, for example =COUNTIFS(A2:A345,"Adelie",B2:B345,"Biscoe"), one formula per cell, then add each row and each column. A pivot table (Insert, then Pivot table, with species under Rows, island under Columns, and species under Values summarized by COUNTA) gives the same counts. Tool: Google Sheets (free) or Excel. Check: The row totals and the column totals both add to 344.
6. Copy your bar chart, then on the copy set the vertical axis minimum to 60 (in Google Sheets, Customize, then Vertical axis, then Min; in Excel, Format Axis, then Bounds, then Minimum). Compare the two charts side by side and note what happens to the Chinstrap bar. Tool: Google Sheets (free) or Excel. Check: On the cropped copy the Chinstrap bar shrinks to a sliver while the counts themselves have not changed.
7. Answer the analysis questions in your document, then paste your tables into an approved chatbot with the prompt in Part 6 and check its answer against the scripted checks. Tool: A document or notebook for your written answers. Check: You have five written answers and a list of the chatbot's errors with corrections.

Fallback route

When to use it: Use this route if the file will not import or no spreadsheet is available.

Work from the model data below, which reports the counts and body-mass summaries from the real file, together with the species-by-island counts. Complete all three scaffold tables, sketch the bar chart on paper with its axis starting at 0, describe the histogram's shape from the summaries, and answer every analysis question and the critique step from them; submit the same items for equal credit.

This route earns the same credit as the primary route.

These summaries of the real file give you every count and value the lab needs without importing it.

Fallback model data

Quantity from the file	Value
Adelie penguins	152 (44 on Biscoe, 56 on Dream, 52 on Torgersen)
Chinstrap penguins	68 (all on Dream)
Gentoo penguins	124 (all on Biscoe)
Recorded body masses	342
Lightest and heaviest body mass	2,700 g and 6,300 g
Middle value and average of the body masses	4,050 g and 4,201.75 g
Number of 500 g bins from 2,500 g to 6,500 g

Part 4 — The Scaffold

Count each species and turn the counts into shares, so you can check that the parts add back to the whole file.

Student scaffold table 1

Species	Count from COUNTIF	Share of the 344 penguins (percent, one decimal)
Adelie
Chinstrap
Gentoo
Total

Record what your formulas and your histogram show about body mass, so you can name its shape with evidence.

Student scaffold table 2

Quantity	Your value or description
Number of recorded body masses
Lightest body mass (g)
Heaviest body mass (g)
Middle value of the masses (g)
Average of the masses (g)
Number of 500 g bins in your histogram
Side where the long, thin tail points
Name of the shape

Count the penguins by species and island at once, so you can read each cell and check the totals both ways.

Student scaffold table 3

Species	Biscoe	Dream	Torgersen	Row total
Adelie
Chinstrap
Gentoo
Column total

Part 5 — Analysis Questions

1. Using your first table, show the division that gives each species' share of the 344 penguins, and check that the three shares add to 100.0%. If they land at 99.9 or 100.1, say why.
2. Describe your histogram of body mass in words: where the main pile of bars sits, which way the long, thin tail points, and how many peaks you see. Then name the shape and say how the middle value and the average back up your answer.
3. Explain why species gets a bar chart with gaps between the bars while body mass gets a histogram with touching bars. Would a pie chart also be honest for the species counts? Say why or why not.
4. From your two-way table, how many penguins were logged on Dream, and which species make up that number? The number 124 appears twice in the table; explain what each 124 counts.
5. Choose one and answer it in 3–4 sentences. (a) Compare your full bar chart with the copy whose axis starts at 60: what impression does the cropped chart give about Chinstrap penguins, and why is it misleading? (b) Your histogram used 500 g bins: how might the picture change with much wider or much narrower bins, and what does that mean for how confidently you can name a shape?

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've pasted my completed Week 2 Data Lab tables above. They come from the Palmer penguins file, which has 344 rows and 8 columns: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, sex, and year. Please do five things. First, give the count and the percentage of penguins in each species. Second, describe the shape of the body mass histogram and name its skew. Third, say whether these data show that living on Biscoe makes penguins heavier. Fourth, as a stretch question for later in the course, say what the chance is that exactly one of two penguins picked at random from the file is a Gentoo. Fifth, also as a stretch question, say how sure we can be about the average body mass of all penguins in the archipelago.

Test the response for these likely failures:

• Chatbots often name the skew by where the pile of values sits, calling body mass left-skewed because most penguins sit at the lighter end of the range.
• Chatbots often report species counts or percentages they never checked, such as round shares like 45%, 20%, and 35%, or counts that do not add to 344.
• Chatbots often slide from a pattern in the two-way table to a cause, saying Biscoe's conditions make penguins heavier because the heavy Gentoo penguins all live there.
• On the stretch chance question, chatbots often multiply the chance of a Gentoo by the chance of a non-Gentoo once and stop, forgetting that the one Gentoo could be the first pick or the second.
• Asked how sure we can be, chatbots often invent an interval and say there is a 95% chance the true average is inside it, or that 95% of penguins fall inside it.

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, charts, or the field log.

Equivalent route (no AI required)

No AI account is required for this lab. Instead of the chatbot, critique this flawed analysis, printed here in full: "The penguin file has 350 penguins: 150 Adelie, 70 Chinstrap, and 130 Gentoo, which is 45%, 20%, and 35%. Body mass is left-skewed, because most of the penguins are bunched at the lighter end. Living on Biscoe makes penguins heavier, since the heaviest species lives there. The chance that exactly one of two random penguins is a Gentoo is the Gentoo chance times the non-Gentoo chance, and nothing more. We can be 95% sure that 95% of all penguins weigh exactly 4,201.75 g." Mark it up: quote each flawed sentence, name what is wrong (an invented statistic, a flipped skew direction, cause read from association, a dropped number of ways, or a misread confidence statement), cite the evidence from your tables, charts, or the field log, and write a corrected sentence beneath it; for the last two sentences, say what the course will check later. This route assesses the same objective (Objective 2 — summarize and display a single quantitative or categorical variable with appropriate tables and graphs, and describe its distribution's shape, center, and spread with the right numerical summaries) 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 bar chart, its cropped copy, and your histogram, or labelled sketches of them
• 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 Data Lab report on the real Palmer penguins field log: three completed tables (species counts and shares that add back to 344, body-mass summaries with the shape named by its tail, and the species-by-island two-way table with totals), a bar chart with its cropped copy and a histogram or labelled sketches of them, written answers to five analysis questions, and a critique of a chatbot's description of the same data, 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
Getting, counting, and sharing the data	The file is opened or the fallback model data is used, the three species counts add back to 344, each share is the count divided by 344 as a percentage to one decimal, and the two-way table's row and column totals both reach 344.	The data are opened and counted, but one or two counts or shares are missing or wrong, or the totals are not checked against 344.	No counts are recorded, or the counts are invented rather than computed.
Building honest pictures	A bar chart of the species starts its axis at 0 and keeps gaps between bars, a histogram of body mass uses equal 500 g bins with touching bars, and the cropped copy is labelled as the misleading version; sketches with labelled axes earn this band equally.	The pictures are present, but one has a flaw such as an axis that does not start at 0, unequal bins, or missing axis labels.	No bar chart or histogram, and no sketch of either, is submitted.
Reading shape and tables	Analysis questions 1 to 4 are answered accurately: the shares are shown and checked, the body-mass shape is named mildly right-skewed by its tail with the middle value and the average as evidence, the choice of bar chart versus histogram is explained, and the Dream total and the two different 124s are read correctly.	The questions are attempted, but one or two answers name the skew by the pile, confuse a cell with a total, or leave out a reason.	The analysis questions are missing or do not address the penguin data.
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, charts, or the field log, 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.
Reflection on how a picture can mislead	The chosen reflection option is answered in 3–4 sentences that connect a specific design choice, the cropped axis or the bin width, to how a reader could be misled.	The reflection is answered but stays general or does not name a specific design choice.	No reflection is submitted.

Quality Gate

• Every count and value in the tables comes from your own formulas or the fallback model data, never from memory or a chatbot.
• The species counts add back to 344, the shares add to 100.0% apart from rounding, and the two-way table's row and column totals both reach 344.
• The bar chart's axis starts at 0, and the histogram's bars touch and share one bin width.
• The shape of body mass is named by the direction of its tail, with the middle value and the average as evidence.
• No statistic, count, 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 charts.