Which type of hypothesis test is used when the alternative hypothesis is stated as not equal to the null value (in either direction)?

Which type of hypothesis test is used when the alternative hypothesis is stated as not equal to the null value (in either direction)?

• A. Two-tail hypothesis test
• B. ANOVA
• C. One-tail hypothesis test
• D. Chi-square test

Answer: (A)

When the alternative hypothesis says the parameter is not equal to the null value, deviations can occur on either side of that value. This means you’re checking for evidence in both directions, so you reject the null if the test statistic is far in either tail of the sampling distribution. That’s a two-tailed hypothesis test. Other options don’t fit this framing: a one-tailed test looks for a bend in only one direction (either greater than or less than the null value). A chi-square test handles categorical data (counts in categories) rather than a parameter value. ANOVA compares means across multiple groups, not the directional question of whether a single parameter differs from a specific value.

When the alternative hypothesis says the parameter is not equal to the null value, deviations can occur on either side of that value. This means you’re checking for evidence in both directions, so you reject the null if the test statistic is far in either tail of the sampling distribution. That’s a two-tailed hypothesis test.

Other options don’t fit this framing: a one-tailed test looks for a bend in only one direction (either greater than or less than the null value). A chi-square test handles categorical data (counts in categories) rather than a parameter value. ANOVA compares means across multiple groups, not the directional question of whether a single parameter differs from a specific value.