A fair coin should land showing tails with a relative frequency of 50% in a long series of flips. Connor reads that spinning - rather than flipping - a US penny on a flat surface is not fair, and that spinning a penny makes it more likely to land showing tails. She spun her own penny 100 times to test this and the penny landed showing tails in 60% of the spins. Let p represent the proportion of spins that this penny would land showing tails.

What are appropriate hypotheses for Connor's significance test?

A. H_0 : p = 50% H_1 : p > 60%

B. H_0: p = 50% H_1: p > 50%

C. H_0: p = 50% H_1: p < 50%

D. H_0 : p = 60% H_1 : p < 60%

Option B is correct

H_0: p = 50% H_1: p > 50%

Explanation:

Here a we are checking if proportion of tails will be high if penny is spinned,

appropriate hypotheses for Connor's significance test: H_0: p = 50% H_1: p > 50%

B. H_0: p = 50% H_1: p > 50%

Explanation:

In knowing if a test is significant, your statistic will be much more than the critical value from the table: Your finding is significant. You discard the null hypothesis. The likelihood is little that the difference or connection occurred by chance, and p is smaller than the critical alpha level (p < alpha ).

Going by the question above we are examining if the proportion of tails will be high in the condition that penny is spinned, the appropriate hypotheses for Connor's significance test: H_0: p = 50% H_1: p > 50%

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