Learning Targets

Standard: CCSS 6.SP.A.1–3 & 6.SP.B.4–5 Time: ~45 min Materials: This activity (device or printed), scratch paper Grade 6
Teacher Notes (not printed)

Pacing

  • Launch (5 min): Read "The Brief." Anchor the context: a data scientist studies air quality (AQI) across the city. Stress that a statistical question expects answers that vary.
  • Analysis work (30–35 min): Students complete Task 1 → 5 in order. Task 5 (the Agency Report) pulls the center and spread results from earlier tasks, so encourage them to check each statistic as they go.
  • Debrief (5–10 min): Discuss why the median is safer than the mean when there is an outlier, and how MAD lets you compare which neighborhood is more consistent.

Differentiation

  • Level 1 (support): Use the green callouts and bilingual (EN/ES) prompts. Provide a printed "order the numbers first" reminder for median, and let students use a calculator for the MAD averaging step.
  • Level 2 (enrichment): Students compare the two neighborhoods using BOTH center and MAD, and justify a data-driven recommendation in the report. They also explain why the Riverside distribution is right-skewed.

STEM Connection

  • This is an authentic data-science / environmental-engineering task: Ask → Collect → Analyze (center + spread) → Visualize → Report. Students do exactly what an environmental data analyst does with real air-quality sensor networks.

Answer key

  • Q1: statistical = B and D (variable); shown as multi-check.
  • Greenfield AQI {42,38,45,40,50,41,44} → sum 300, mean 300÷7=42.857≈42.9, median 42 (4th of sorted 38,40,41,42,44,45,50), no mode. MAD = 20.857÷7 = 2.98 ≈ 3.0.
  • Riverside AQI {35,38,40,37,39,41,98} → sorted 35,37,38,39,40,41,98; median 39, mean 328÷7=46.857≈46.9; outlier 98 → use median. Range 63. MAD = 102.286÷7 = 14.6.
  • Histogram: 30–39 bin has the most days (count 4); 40–49 has 2; 90–99 has 1.
  • Box plot Greenfield: min 38, Q1 40, med 42, Q3 45, max 50. IQR = 5.
Unit 8 · Math Architect · Statistics (6.SP)

Data Challenge: The City Air Quality Lab

You are a junior data scientist at the City Environmental Agency. Air-quality sensors across two neighborhoods send a stream of daily AQI readings. Your job: turn that raw data into trustworthy statistics, build the right graphs, and write a report that tells the city where the air is cleaner — and which neighborhood is more consistent.

6.SP.A.1–3 6.SP.B.4–5 Mean · Median · Mode MAD & Spread Dot · Histogram · Box plot
1 · AskSort statistical from non-statistical questions.
2 · CenterFind mean, median & mode of the readings.
3 · SpreadMeasure variability with range & MAD.
4 · VisualizeRead the histogram & box plot.
5 · ReportCompare neighborhoods & recommend.
Analyses verified: 0 / 8

The Brief

The agency sends you one week of daily readings from each neighborhood's sensor. The number is the Air Quality Index (AQI) — lower is cleaner air. Every task below uses this same field data set.

AQI scale  0–50 = Good (green)  ·  51–100 = Moderate (yellow)  ·  lower = cleaner air

Sensor field data — daily AQI

Greenfield Park · 7 days

42 38 45 40 50 41 44

Riverside Flats · 7 days

35 38 40 37 39 41 98
Deliverable 1
Report the center (mean & median) for each neighborhood.
Deliverable 2
Report the spread (range & MAD) and handle the outlier.
Deliverable 3
Recommend the cleaner, more consistent neighborhood.
Level 1 · Support

A data set is just a list of numbers collected by asking the same question many times. The center tells you a typical value; the spread tells you how much the values bounce around.

Español: Un conjunto de datos es una lista de números. El centro indica un valor típico; la dispersión indica cuánto varían los datos.

Task 1 · Ask the Right Question Statistical questions

A statistical question is one you expect to get many different answers to — its data varies. Before you collect AQI data, decide which of these field questions are statistical. Select all that are statistical, then press Check.

Level 1 · Support

Ask yourself: "Would this question get one answer or many different answers?" One answer = not statistical. Many varying answers = statistical.

Español: ¿La pregunta tiene una respuesta o muchas respuestas diferentes? Muchas respuestas que varían = pregunta estadística.

Task 2 · Find the Center Mean · Median · Mode

Start with Greenfield Park. The dot plot below shows the seven daily readings. Find the three measures of center, then read the dotted mean line to check yourself.

36 40 44 48 52 AQI (Air Quality Index) mean ≈ 42.9
Greenfield · 7 readings1 dot = 1 day

Q2.1 — Mean of Greenfield (round to the tenth)

AQI

Q2.2 — Median of Greenfield

AQI

Level 1 · Support

Mean = add all 7 numbers, then divide by 7. Median = put the numbers in order and find the middle one. With 7 values, the middle is the 4th.

Español: Media = suma los 7 números y divide entre 7. Mediana = ordena los números y toma el del medio (el 4.º).
Level 2 · Enrichment

The mode is "no mode" here — every reading appears once. When would a city analyst actually care about the mode instead of the mean? (Hint: think about the most common alert color, not a typical number.)

36 44 52 60 68 AQI (Air Quality Index) mean ≈ 42.9
Drag the dots · 7 readings 1 right = ~0.5 AQI

Build your own data set. Grab any dot and slide it along the AQI axis. Watch the dashed mean line and the live readout move with it — the mean is the balance point of all seven readings.

Live mean
42.9
Range
12
Level 1 · Support

Drag one dot to the right (a higher AQI). The dashed mean line slides right too — one big reading pulls the mean up. Drag it back and the mean drops.

Español: Arrastra un punto a la derecha (AQI más alto). La línea de la media se mueve con él. Un valor grande sube la media.
Level 2 · Enrichment

Drag dots until the mean reads exactly 50 but the range stays 12 or less. Is more than one data set possible? Explain why the mean can match while the dots differ.

Task 3 · Measure the Spread Range & MAD

The mean alone hides how much the air bounces around day to day. Measure Greenfield's variability. The MAD worktable below walks you through it: each |deviation| is the distance of a reading from the mean (42.857).

Q3.1 — Range of Greenfield (max − min)

AQI

MAD worktable — distance from the mean (42.857)

Day AQI Mean |deviation|
42 42.857 0.857
38 42.857 4.857
45 42.857 2.143
40 42.857 2.857
50 42.857 7.143
41 42.857 1.857
44 42.857 1.143
Sum of |deviations| 20.857

Q3.2 — MAD of Greenfield = sum of |deviations| ÷ 7 (round to the tenth)

AQI

Center (mean)
≈ 42.9
Typical spread (MAD)
≈ 3.0

Read it like an analyst: "Greenfield's AQI is about 43, give or take 3." You will compare this MAD against Riverside's spread in your final report.

Level 1 · Support

MAD = mean absolute deviation. Step 1: find each reading's distance from the mean (already done in the table). Step 2: average those distances (add the |deviations|, divide by 7).

Español: MAD = desviación media absoluta. Suma las distancias a la media y divide entre 7.
Level 2 · Enrichment

A small MAD means a consistent sensor; a big MAD means the air swings a lot. Predict: will Riverside's MAD be larger or smaller than Greenfield's, and why? (Look at that 98 reading.)

Task 4 · The Outlier & the Histogram Distribution shape

Now look at Riverside Flats: 35, 38, 40, 37, 39, 41, 98. One sensor day spiked to 98 (a nearby brush fire). The histogram below bins the seven readings into AQI ranges so you can see the distribution's shape.

0 1 2 3 4 30s 40s 50s 60s 70–80s 90s AQI range (bin width 10) outlier
Riverside · histogram1 bar = days in range

Q4.1 — Median of Riverside (order all 7, take the middle)

AQI

Q4.2 — Mean of Riverside (round to the tenth)

AQI

Analyst's insight: the median is 39 but the mean jumps to 46.9 — that one fire-day reading of 98 drags the mean upward. When a distribution has an outlier, the median describes the typical day more honestly.

Level 2 · Enrichment

The histogram has most readings in the 30s–40s, then a gap and a single bar way out at 90s. That makes the distribution right-skewed. Explain in one sentence why the mean ends up greater than the median for a right-skewed shape.

Task 5 · Build the Box Plot Five-number summary

For the city dashboard you need a box plot of Greenfield's week. The five-number summary is drawn below from the ordered data 38, 40, 41, 42, 44, 45, 50. Read the plot and confirm the key values.

36 40 44 48 52 AQI 38 40 42 45 50
Greenfield · box plotmin · Q1 · med · Q3 · max

Q5.1 — Interquartile range = Q3 − Q1 (the box width)

AQI

Level 1 · Support

A box plot shows five points: min, Q1, median, Q3, max. The box holds the middle half of the data. Its width is Q3 − Q1. The whiskers stretch to the smallest and largest readings.

Español: La caja contiene la mitad central de los datos. Su ancho es Q3 − Q1. Los bigotes llegan al mínimo y al máximo.
Level 2 · Enrichment

Greenfield's box plot is short and centered (IQR = 5). Riverside's would have a tiny box but a whisker stretched all the way to 98. What does the length of a whisker tell a city planner about that neighborhood's air?

Task 6 · The Agency Report Compare & recommend

Bring your statistics together in the city report card. Enter the two missing values; the comparison verdict updates live so you can see which neighborhood the data supports.

Statistic Greenfield Riverside
Median (typical day) 42 39
Mean 42.9 46.9
Range (max − min) 63
MAD (consistency) 3.0

Greenfield range = 50 − 38. Compute it and enter it to confirm you can pull spread from raw data.

Lower typical AQI
More consistent

Level 2 · Enrichment

Riverside has the lower median (39 vs 42) — its typical day is cleaner. But its MAD is 14.6 vs Greenfield's 3.0, so its air is far less consistent. Write your recommendation: which neighborhood would you call "reliably good air," and which statistic settles it — center or spread?

Level 1 · Support

Lower median = cleaner typical day. Smaller MAD = steadier, more consistent air. Compare the two columns to fill the verdict.

Español: Mediana más baja = aire más limpio típico. MAD más pequeño = aire más constante.

Data Scientist's Sign-off

When every analysis checks out, file your report with the city. Enter your name in the field below, then press Submit report & grade to save your score as a PDF or DOC.

Performance Rubric — Air Quality Data Challenge (6.SP)

Level Score Descriptor
4 — Exceeds 8 / 8 Sorts statistical questions correctly and computes mean, median, range, MAD, and IQR accurately for both data sets. Reads the histogram and box plot, explains why the outlier makes the median the better measure, and writes a data-driven recommendation using both center and spread.
3 — Meets 6–7 / 8 Computes most measures of center and spread with at most one arithmetic slip. Reads the graphs and reaches a reasonable recommendation.
2 — Approaching 4–5 / 8 Finds simple measures (mean, median, range) but struggles with MAD or with interpreting the outlier and distribution shape. Partial report.
1 — Beginning 0–3 / 8 Few correct statistics. Confuses mean with median, or cannot order data to find the median. Needs reteaching on measures of center, spread, and reading data displays.