You collected data from a random sample of students on their impressions of the university. On a particular opinion item item, the mean for male students was 15.2 -- with a standard deviation of 3.4. The mean on that item for women was 14.4, with a standard deviation of 3.8. Calculate Cohen's d effect size. IN THE SPACE BELOW, write the effect size AND your interpretation of it.
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!
You collected data from a random sample of students on their impressions of the university.
On a particular opinion item item, the
The mean on that item for women was 14.4, with a standard deviation of 3.8.
Calculate Cohen's d effect size. IN THE SPACE BELOW, write the effect size AND your interpretation of it.
The formula for Cohen’s d is,
d = (M1 – M2)/spooled, where M1 and M2 are the means of group 1 and 2, respectively, and spooled is the pooled standard deviation, that is, √[(s12+ s22) / 2], where s1 and s2 are the standard deviation of groups 1 and 2, respectively.
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