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Answer :
Final answer:
The best suited hypothesis for the test would be option a) H0: The average weight of an SUV is 1,940 kg and H1: The average weight of an SUV is not equal to 1,940 kg. By performing a t-test, we can compare the sample mean to the hypothesized population mean and determine whether we can reject the null hypothesis at a chosen significance level.
Explanation:
The appropriate hypotheses for this test would be option a. In statistical testing, the null hypothesis (H0) is the statement that there is no significant difference or effect, and in this case, we are asserting that the average weight of a new SUV is 1,940 kg. The alternative hypothesis (H1) is the statement we accept if the null hypothesis is proven unlikely, which in this scenario is the claim that the average weight of a new SUV is not equal to 1,940 kg.
To validate either hypothesis, we would perform a t-test. This test compares the mean of the sample to the hypothesized population mean (1,940 kg), taking into account the sample size and standard deviation. If the resulting p-value is less than the significance level (typically 0.05), we reject the null hypothesis in favor of the alternative, providing evidence that the true average weight differs from 1,940 kg.
Learn more about Hypothesis Testing here:
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