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Answer :
To decide whether to reject or accept the null hypothesis [tex]H_0[/tex] in a right-tailed test, we need to compare the calculated [tex]Z[/tex]-value with the [tex]Z[/tex]-critical value.
Here's a step-by-step explanation:
Understanding the Hypotheses:
- Typically, [tex]H_0[/tex] (the null hypothesis) might be: 'There is no effect' or 'There is no difference.'
- The alternative hypothesis [tex]H_A[/tex] in a right-tailed test suggests that there is an increase or a greater effect.
Comparing [tex]Z[/tex] Values:
- Calculated [tex]Z[/tex]: This is the [tex]Z[/tex]-score you obtained from your test, which is 1.73.
- Critical [tex]Z[/tex]: This is the [tex]Z[/tex]-score that represents the cut-off point for significance, which is 1.64 in this case.
Decision Rule for Right-Tailed Test:
- If the calculated [tex]Z[/tex] is greater than the [tex]Z[/tex]-critical value, you reject [tex]H_0[/tex].
- If the calculated [tex]Z[/tex] is less than or equal to the [tex]Z[/tex]-critical value, you fail to reject [tex]H_0[/tex].
Applying the Decision Rule:
- Since the calculated [tex]Z[/tex] (1.73) is greater than the [tex]Z[/tex]-critical (1.64), we reject [tex]H_0[/tex].
Conclusion:
- By rejecting [tex]H_0[/tex], you are concluding that there is sufficient evidence to support the alternative hypothesis that there is an effect or increase in this context.
In summary, the decision is to reject the null hypothesis [tex]H_0[/tex].
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