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. Is the null hypothesis more or less likely to be​ rejected? Explain. Less likely; for degrees of freedom less than​ 30, the tail of the curve are thicker for a t-sampling distribution.​ Therefore, if you incorrectly use a standard normal sampling​ distribution, the area under the curve at the tails will be larger than what it would be for the​ t-test, meaning the critical​ value(s) will lie closer to the mean. Is the result the​ same? The result is different. With a​ two-tailed case, the tail thickness does not affect the location of the critical​ values, however, in a​ left- and​ right-tailed case, the tail thickness does affect the location of the critical value. The result is different. With a​ left- and​ right-tailed case, the tail thickness does not affect the location of the critical​ value, however, in a​ two-tailed case, the tail thickness does affect the location of the critical value. The result is the same. In each​ case, the tail thickness affects the location of the critical​ value(s). The result the same. In each​ case, the tail thickness does not affect the location of the critical​ value(s).