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Statistics and probability

Course: Statistics and probability > Unit 14

Lesson 2: Chi-square tests for relationships

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)

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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
	Trucks	Sedans
Red	37	57
Expected	47, point, 0	47, point, 0
Blue	36	41
Expected	38, point, 5	38, point, 5
Black	77	48
Expected	62, point, 5	62, point, 5
Other	30	34
Expected	32, point, 0	32, point, 0

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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?

(Choice A)
This is convincing evidence that color and type of car are not independent.
(Choice B)
We lack evidence to say that color and type of car are not independent.
(Choice C)
This is convincing evidence that the distribution of color differs between trucks and sedans in this population.
(Choice D)
This isn't enough evidence to say that the distribution of color differs between trucks and sedans in this population.
(Choice E)
Buying certain types of cars causes people to be more likely to choose certain colors.

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Statistics and probability

Course: Statistics and probability > Unit 14

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