You need to find Seattle's rainfall in March from a table listing cities as rows and months as columns. What is the correct procedure?
AFind any cell labeled 'March' and read its value
BLocate the Seattle row and the March column, then read the value at their intersection
CAdd all values in the Seattle row until you count to the third column
DFind the column labeled 'Seattle' and look for March
Every cell's meaning comes from two coordinates: its row and its column. The correct method is to identify the row (Seattle) and the column (March) independently, then find where they meet. Option A skips the row check — any 'March' cell belongs to a specific city, and you need Seattle's. Option D gets rows and columns reversed, a very common error.
Question 2 Multiple Choice
A student reads '28' from a sports stats table under a column she thinks says 'points.' Her answer seems surprisingly low for a season total. What should she do?
AAccept 28 since that is what the table shows
BRe-read the column header carefully to check whether it says 'points per game' rather than 'total season points,' and verify the units before accepting the value
CAdd 28 to the next row's value to get a higher total
DAssume the table contains an error and find a different source
When a table value seems wrong, the first action should always be re-reading the header. 'Points per game' and 'total season points' can look similar in a header but mean entirely different things. A player averaging 28 points per game over 82 games would have 2,296 total — if you needed the season total, reading the per-game column produces a dramatically wrong answer. Headers define what the numbers mean.
Question 3 True / False
The row and column headers in a data table are optional labels — the numbers in the cells are meaningful on their own.
TTrue
FFalse
Answer: False
Without headers, a number in a table is meaningless. The value '342' could be dollars, miles, people, points, or anything else. Headers define the subject (row) and the attribute (column) for every cell. Reading headers is not a preliminary step you can skip — it is the step that makes every number interpretable.
Question 4 True / False
To identify a trend in a data table — such as whether sales increased over several months — you compare values across multiple cells in the same row or column rather than reading just one cell.
TTrue
FFalse
Answer: True
A trend is a pattern across multiple values. A single cell tells you one data point; a trend requires comparing several points in sequence — consecutive months in a row, or multiple years in a column. Identifying trends is one of the most valuable things data tables enable, and it always requires looking across more than one cell.
Question 5 Short Answer
Why is it essential to read both the row header AND the column header before recording any value from a data table?
Think about your answer, then reveal below.
Model answer: Each cell sits at the intersection of a row and a column. The row header tells you what subject or category is described; the column header tells you what attribute or measurement is recorded. Reading only one of the two headers gives you an incomplete address — you might end up in the right row but the wrong column, or vice versa. Together, the two headers form the complete identity of any cell's value.
This two-coordinate navigation habit is the foundational skill for all table reading. It directly prevents the most common error (reading the right row but wrong column) and also prevents misinterpreting units (reading a 'per game' column when you need a 'season total' column). Any surprising answer should trigger a return to both headers.