It is known that roughly 2/3 of all human beings have a dominant right foot or eye. Is there also right-sided dominance in kissing behavior? An article reported that in a random sample of 115 kissing couples, both people in 70 of the couples tended to lean more to the right than to the left. (Use a = 0.05.) A USE SALT places.) (a) If 2/3 of all kissing couples exhibit this right-leaning behavior, what is the probability that the number in a sample of 115 who do so differs from the expected value by at least as much as what was actually observed? (Round your answer to four decimal (b) Does the result Štate the appropriate null and alternative hypotheses. Ho: p= 2/3 Hại p. 2/3 Ho: p- 2/3 Hại p< 2/3 the experiment suggest that the 2/3 figure is implausible for kissing behavior? Ho: P- 2/3 H ps 2/3 Ho: p- 2/3 Hại p > 2/3 Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to four decimal places.) P.value - State the conclusion in the problem context. Do not reject the null hypothesis. There is sufficient evidence to conclude that the true proportion of right-leaning behavior differs from 2/3. Do not reject the null hypothesis. There is not sufficient evidence to conclude that the true proportion of right-leaning behavior differs from 2/3. Reject the null hypothesis. There is not sufficient evidence to conclude that the true proportion of right-leaning behavior differs from 2/3. Reject the null hypothesis. There is sufficient evidence to conclude that the true proportion of right-leaning behavior differs from 2/3.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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