Judging what a study design supports: random sampling vs. random assignment, causation vs. correlation, and generalizability.
21
Total questions
8
Easy
8
Medium
5
Hard
These questions describe how a study was run and ask what conclusion the design supports. The two levers are random selection (lets you generalize to the population) and random assignment to treatment groups (lets you claim cause and effect). Each is independent of the other.
Build the two-question habit: Were subjects randomly selected? If not, conclusions don't generalize beyond the participants. Were treatments randomly assigned? If not, the study can show association but never causation. An observational study — however large — cannot support a causal claim; only a randomized experiment can.
Straight from the Grind1600 question bank — try each one before revealing the answer.
Correct answer: D
Choice D is correct. Families at a veterinary clinic are more likely to own pets than households in the neighborhood generally, so the sample isn't representative and the estimate is likely biased upward.
Choice A is incorrect. A sample mean estimates the population mean; it doesn't establish it, and here the sample is drawn from a group unusually likely to own pets.
Choice B is incorrect. The problem isn't the number of families surveyed but where they were found. A larger sample drawn the same way would carry the same bias.
Choice C is incorrect. This is the opposite of the situation. Recruiting at a veterinary clinic is exactly what makes the method flawed.
Correct answer: A
Choice A is correct. A random sample gives an estimate, not a guaranteed match to the population. Because a different random sample of 500 adults could produce a different percentage, none of the three statements must be true.
Choice B is incorrect. Statement I need not be true; 62% is the sample's result, and the population percentage may differ.
Choice C is incorrect. Statement II need not be true either, since repeating the survey with a different random sample can yield a different percentage.
Choice D is incorrect. None of the three statements is guaranteed, so selecting all of them is incorrect.
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.
Scatterplots & Two-Variable Data
Reading scatterplots, lines of best fit, interpreting slope in context, and distinguishing linear from exponential association.
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.
21 Evaluating Statistical Claims questions with step-by-step explanations, woven into a day-by-day study plan built for your test date.
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