You are testing a claim and incorrectly use the normal sampling distribution instead of the t-sampling distribution. Does this make it more or less likely to reject the null hypothesis? Is this result the same no matter whether the test is left-tailed, right-tailed, or two-tailed? Explain your reasoning.

From the given data, the typical appropriation is utilized rather than t distribution for testing. The thicknesses of the curve similarly influence both normal distribution and territory of t distribution. The normal distribution test and t test give a similar dismissal for the invalid theory for any tail of the test. Besides, the tests normal sampling distribution and t sampling distribution give a similar dismissal to null hypothesis.  

Along these lines, the outcomes got by utilizing normal distribution and t distribution are distinguished as same and for each situation, the tail thickness doesn't influence the event of the basic qualities.

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Step-by-step explanation:

The vital t-values are most of the time more extreme than the resultant critical z-values, hence it is expected to be less likely to refuse the null hypothesis (given that the value of the test statistic are still unchanged).

This outcome will remain unchanged no matter whether the test is right-, left-, or two-tailed, since the negative critical t-values will be lesser when compared to the negative critical z-values and the positive critical t-values will be higher than the positive critical z-values.

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