Suppose a mutual fund qualifies as having moderate risk if the standard deviation of its monthly rate of return is less than 3%. A mutual-fund rating agency randomly selects 29 months and determines the rate of return for a certain fund. The standard deviation of the rate of return is computed to be 2.23%. Is there sufficient evidenc to conclude that the fund has moderate risk at the a = 0.05 level of significance? A normal probability plot indicates that the monthly rates of return are normally distributed. What are the correct hypotheses for this test? The null hypothesis is Ho: The alternative hypothesis is H,: Calculate the value of the test statistic. X = |(Round to two decimal places as needed.) Use technology to determine the P-value for the test statistic. The P-value is. (Round to three decimal places as needed.) What is the correct conclusion at the a = 0.05 level of significance? Since the P-value is than the level of significance, the null hypothesis. There V sufficient evidence to conclude that the fund has moderote rick ot the 0. 05 level of cianifieones
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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