What is true about t distributions? a. There is more than one t distribution (i.e. more than one t density curve) and they are all symmetric and centered at 0. b. As sample size increases, the t density curve approaches the standard Normal density curve. c. The spread of the t distributions is a bit greater than that of the standard Normal distribution. d. All of the above.
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!
What is true about t distributions?
a. There is more than one t distribution (i.e. more than one t density curve) and they are all symmetric and centered at 0.
b. As
c. The spread of the t distributions is a bit greater than that of the standard
d. All of the above.
The correct answer is option d.
that is, all the above.
For a t distribution the following holds true.
a. There is more than one t distribution (i.e. more than one t density curve) and they are all symmetric and centered at 0.
b. As sample size increases, the t density curve approaches the standard Normal density curve.
c. The spread of the t distributions is a bit greater than that of the standard Normal distribution.
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