Reading scatterplots, lines of best fit, interpreting slope in context, and distinguishing linear from exponential association.
35
Total questions
13
Easy
15
Medium
7
Hard
Scatterplot questions give you plotted data with (usually) a line of best fit and ask you to interpret its slope or intercept in context, predict a value, compute the difference between an actual data point and the line's prediction, or judge whether a linear or exponential model fits the association.
The line of best fit is a prediction machine: for a given x, the line's height is the predicted y, and (actual − predicted) is the residual questions love to ask about. Slope-in-context follows the standard recipe — predicted change in y per one unit of x. Count carefully on the axes; most errors here are reading errors, not concept errors.
Straight from the Grind1600 question bank — try each one before revealing the answer.
Correct answer: D
Choice D is correct. A scatterplot is used to display the relationship between two quantitative variables. Since both hours of sunlight and plant height are quantitative, a scatterplot is the most appropriate.
Correct answer: A
Choice A is correct. Since h(x) = 0.80 × h(x − 1), each output is 0.80 times the previous output. This represents a constant multiplicative factor less than 1, so the function decreases exponentially. Choice B is incorrect because a linear function would decrease by a constant amount, not a constant factor. Choices C and D describe increasing functions, which contradicts the 0.80 multiplier.
Ratios, Rates & Units
Setting up proportions, converting units, and reasoning with rates — the most common word-problem machinery on the SAT Math section.
Percentages
Percent change, percent of a quantity, reverse-percentage problems, and multi-step percent scenarios like tax-plus-discount.
Data Distributions & Measures of Center
Mean, median, mode, range, and standard deviation — and how outliers or skew change them — read from lists, tables, and frequency plots.
Probability
One-event and conditional probability, usually read out of two-way frequency tables — the key is identifying the correct restricted group.
Inference & Margin of Error
What sample results let you conclude about a population, how margin of error works, and why sample size changes confidence.
Evaluating Statistical Claims
Judging what a study design supports: random sampling vs. random assignment, causation vs. correlation, and generalizability.
35 Scatterplots & Two-Variable Data questions with step-by-step explanations, woven into a day-by-day study plan built for your test date.
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