STATISTICAL TECHNIQUES AND TOOLS
CHI SQUARE
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which statement is NOT correct about the chi-square test statistic?
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A value close to 0 would indicate expected counts are much different from observed counts.
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A large value of the test statistic would be in support of the alternative hypothesis.
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A small value of the test statistic would indicate evidence supporting the null hypothesis.
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The test statistic is the sum of positive numbers and therefore must be positive.
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Explanation:
Detailed explanation-1: -If the expected is actually zero and the observed is not zero, the chi-square value would be infinity. This is as it should be: you’re observing something that according to the model is impossible, so it should automatically reject.
Detailed explanation-2: -The chi-square distribution curve is skewed to the right, and its shape depends on the degrees of freedom df. For df > 90, the curve approximates the normal distribution. Test statistics based on the chi-square distribution are always greater than or equal to zero.
Detailed explanation-3: -What conclusion is appropriate if a chi-square test produces a chi-square statistic near zero? There is a good fit between the sample data and the null hypothesis.
There is 1 question to complete.