Which of the following statements are correct? 1. There are several different types of Normal distributions, each of which is absolutely defined (or identified) by two numbers: the mean u and standard deviation o. 2. A standard Normal distribution is a special type of Normal distribution with u = 0 and o = 1. 3. Standardizing a Normal variable X generates a new random variable, denoted by z, that has the standard Normal distribution. (That is, if X is Normally distributed, we can use the formula z = (x-µ)/o to convert an observation x to a z-value, and z is Normally distributed with u = 0 and o = = 1.) 4. The z-scores (or z-values) of the standard Normal distribution range from positive infinity to negative infinity. 5. A researcher should not presume that the data obtained are automatically Normally distributed- the researcher should first plot the data to see whether the histogram, stemplot or dotplot is roughly bell-shaped before calculating probabilities using the Normal distribution.
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!
![Which of the following statements are correct?
1. There are several different types of Normal
distributions, each of which is absolutely
defined (or identified) by two numbers: the
mean p and standard deviation o.
2. A standard Normal distribution is a special type
of Normal distribution with u = 0 and o = 1.
3. Standardizing a Normal variable X generates a
%3D
new random variable, denoted by z, that has
the standard Normal distribution. (That is, if X is
Normally distributed, we can use the formula z
= (x-u)/o to convert an observation x to a
z-value, and z is Normally distributed with u =
O and o = 1.)
4. The z-scores (or z-values) of the standard
Normal distribution range from positive infinity
to negative infinity.
5. A researcher should not presume that the data
obtained are automatically Normally
distributed- the researcher should first plot the
data to see whether the histogram, stemplot or
dotplot is roughly bell-shaped before calculating
probabilities using the Normal distribution.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fafee4775-f07d-4d9c-bb1d-2e9dcf7f7590%2F4180da19-14db-47ad-b2de-c7dcbc394d34%2Fnwsc54_processed.jpeg&w=3840&q=75)
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