The research question is whether attractiveness affects the behavior of infants looking at photographs of women’s faces. The researcher is expecting the infants to prefer the more attractive face. Therefore, the researcher predicts that the infants will spend more than half of the 20-second period looking at the attractive face. Specifically, the researcher tested a sample of n = 9 infants and obtained a mean of M = 13 seconds looking at the attractive face with SS = 72. Report the critical t-value for the alpha level at 0.01.
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!
The research question is whether attractiveness affects the behavior of infants looking
at photographs of women’s faces. The researcher is expecting the infants to prefer the
more attractive face. Therefore, the researcher predicts that the infants will spend
more than half of the 20-second period looking at the attractive face. Specifically, the researcher tested a sample of n = 9 infants and obtained a mean of M = 13 seconds looking at the attractive face with SS = 72.
Report the critical t-value for the alpha level at 0.01.
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