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Making conclusions in chi-square tests for two-way tables

AP.STATS: DAT‑3 (EU), DAT‑3.L (LO), DAT‑3.L.1 (EK), DAT‑3.L.2 (EK), VAR‑8 (EU), VAR‑8.J (LO), VAR‑8.J.1 (EK), VAR‑8.J.2 (EK)


A market researcher was curious about the colors of different types of vehicles. They obtained a random sample of 180 sedans and a separate random sample of 180 trucks. Here is a summary of the colors in each sample and the results from a chi-squared test:
Chi-square test: Color vs. type
Expected47, point, 047, point, 0
Expected38, point, 538, point, 5
Expected62, point, 562, point, 5
Expected32, point, 032, point, 0
\chi, squared, equals, 11, point, 558, comma, start text, space, D, F, end text, equals, 3, comma, start text, space, P, negative, v, a, l, u, e, end text, equals, 0, point, 009
Assume that all conditions for inference were met.
At the alpha, equals, 0, point, 05 significance level, what is the most appropriate conclusion to draw from this test?
Choose 1 answer: