Turning Field Data Into an Argument · seed 1 · A4, ink-friendly. The answer key prints on its own page for grown-ups.

Making honest arguments from field data

Geography · People & Environments · ages 14-16
Name ______________________   Date ____________
  1. Scatter-plot points cluster tightly around a rising straight line. How would you describe the relationship?

    • A weak negative linear relationship
    • No relationship between the paired measurements
    • A strong positive linear relationship
  2. You measured pebble lengths in centimetres and grouped them into equal-width size intervals. Which graph shows the distribution of lengths?

    • A histogram showing the count in each length interval
    • A scatter plot of pebble length against width
    • A time series showing the order of discovery
  3. The fact that two measurements rise together always proves that one caused the other.

    Circle one:   True   False

  4. In one park, 18 of 24 people asked on a hot afternoon chose shade. Which conclusion fits those replies?

    • Most visitors everywhere choose shade.
    • Most respondents chose shade that afternoon.
    • Trees caused every choice of shade.
  5. You counted shop entries during equal ten-minute periods each hour. You want to show how the counts changed through the day. Which display fits?

    • A histogram grouping entry counts by size
    • A time series of the hourly counts
    • A pie chart of each hour's share of all entries
  6. A scatter plot with no clear upward or downward pattern justifies a rising trend line.

    Circle one:   True   False

  7. A bus campaign forum gets 60 volunteer survey replies. A chart labels their views as the whole town's views. What is the main problem?

    • Sixty replies cannot describe any group.
    • Opinion charts cannot provide evidence about any views.
    • Forum volunteers may not represent the town.
  8. You counted entries at one shop entrance for one hour on a sunny afternoon. Which claim can that count directly support?

    • The recorded entries at that entrance in that hour
    • The usual shopping frequency of the town's residents
    • The seasonal change in visitor numbers across all shops
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Answer key

For grown-ups. Fold this page away before handing over the rest.

Making honest arguments from field data W1-mt_A1qZ6jJ472-s1

  1. A strong positive linear relationship · A rising pattern shows a positive direction. Tight clustering around a straight line shows a strong linear relationship.
  2. A histogram showing the count in each length interval · A histogram shows how many measured lengths fall in each numerical interval. The other displays answer different questions.
  3. False · An association does not establish cause. Another factor may affect both measurements.
  4. Most respondents chose shade that afternoon. · 18 is more than half of 24, so most respondents chose shade. The replies do not establish a cause or describe every town.
  5. A time series of the hourly counts · A time series keeps the hours in order and shows the count at each time. Equal counting periods make those counts comparable.
  6. False · A rising line would suggest a direction these points do not clearly show. Scattered points can support a trend, but a rising pattern must be present.
  7. Forum volunteers may not represent the town. · The forum and voluntary response may select people with particular views. Reporting 60 replies does not establish that they represent the town.
  8. The recorded entries at that entrance in that hour · The observation covers one entrance and one hour. It does not measure town-wide shopping habits or seasonal change.
Worksheet · LightMySky