NC Math 1: a complete guide to descriptive statistics
A deep-dive NC Math 1 EOC guide to descriptive statistics (Statistics and Probability, about 18 to 20 percent of the test). Covers representing one-variable data with dot plots, histograms, and box plots, comparing center and spread, two-way frequency tables, scatter plots and lines of best fit, and the correlation coefficient with the correlation-versus-causation caution.
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What this strand demands
This guide covers descriptive statistics on the NC Math 1 EOC, drawing on Interpreting Categorical and Quantitative Data (NC.M1.S-ID). The Statistics and Probability category is about 18 to 20 percent of the test, a reliable block that rewards careful reading of displays and clear interpretation. Each dot-point page has its own practice: representing data distributions, comparing center and spread, two-way frequency tables, scatter plots and linear models, and correlation and causation.
Representing one-variable data
Three displays show data on a single variable. A dot plot stacks a dot per value; a histogram groups values into bins and shows frequency; a box plot displays the five-number summary (minimum, , median, , maximum) with the box spanning the IQR. Shape is symmetric, skewed right (high-value tail), or skewed left (low-value tail), and may include outliers.
Comparing center and spread
Center is the mean (sensitive to outliers) or median (resistant). Spread is the range (max minus min) or IQR (, resistant). For skewed data or outliers, prefer the median and IQR. To compare two data sets, report both a center and a spread using the same measures for each.
Two-way frequency tables
A two-way table cross-classifies two categorical variables. A joint frequency is one inner cell over the grand total; a marginal frequency is a margin total over the grand total; a conditional frequency divides a cell by its row or column total ("of those who..."). Comparing conditional frequencies across groups reveals association.
Scatter plots and lines of best fit
A scatter plot shows two numerical variables. Describe the direction (positive or negative), form (linear or not), and strength. Fit a line of best fit to predict; interpret the slope as the predicted change in per unit of and the y-intercept as the predicted at .
Correlation and causation
The correlation coefficient (from to ) measures the strength and direction of a linear relationship: sign for direction, size for strength. A strong correlation does not prove causation, a lurking variable, reverse causation, or coincidence can explain it. A residual (observed minus predicted) checks fit: small random residuals mean a good line.
How this strand is examined
- Gridded response. Compute a mean, median, IQR, relative frequency, or prediction. Exact-match scoring.
- Multiple choice and multiple select. Identify shape, choose a measure, interpret slope or , or spot a correlation-causation error.
- Technology-enhanced. Build a box plot or table, or match scatter plots to descriptions.
Check your knowledge
Work these as you would for credit on the EOC.
- A five-number summary is . Find the IQR. (1 point)
- Find the mean and median of , and say which is more representative. (2 points)
- A histogram has a long tail toward high values. Name the shape. (1 point)
- Of students, play music and also a sport. What is this joint relative frequency? (1 point)
- Of musicians, play a sport. What is this conditional relative frequency? (1 point)
- A line of best fit is . Interpret the slope. (1 point)
- Using , predict when . (1 point)
- What does indicate? (1 point)
Sources & how we know this
- North Carolina Standard Course of Study for Mathematics β NC Department of Public Instruction (2024)
- EOC NC Math 1 and NC Math 3 Test Specifications β NC Department of Public Instruction (2024)