Explain what the coefficient of variation is.-What is the advantage of using it compared to standard deviation?

Chapter 1
1. Explain the difference between a population and a sample (from a
statistical point of view).
2. Explain the difference between quantitative variable
and qualitative variable. 
3. Explain the difference between descriptive statistics
and inferential statistics.
Chapter 2
1. For a dataset, without constructing of the frequency distribution table;
how to obtain the class width of frequency distribution table if the
number of classes is given?
Note: Use the formula in the slides; here frequency distribution table is
not provided.
2. Explain the difference between a frequency distribution table and a
relative frequency distribution table
Chapter 3
1. Explain the difference between mean and median. Is mean always
larger than median?
2. Explain the difference between μ and x . How do you determine
which is appropriate to use in a problem?
3. Explain the difference between σ and s. How do you determine which
is appropriate to use in a problem?
4. What is the relationship between variance and standard deviation?
5. Explain the difference between range and interquartile range.
6. Explain what the coefficient of variation is. What is the advantage of
using it compared to standard deviation?
Chapter 4
1. Explain the meaning of “Event with equally likely outcomes”.
2. Explain the difference between joint(nonexclusive) events and
disjoint(mutually exclusive) events.
3. Explain the difference between P(A) and P(A|B). What does it mean
if they are equal in value? What does it mean if they are unequal in
value?
4. Explain the difference between P(A|B) and P(B|A). Must they be equal in value?
5. Explain the difference between Permutation and Combination.
Chapter 5
1. Explain what a discrete random variable is. List examples.(4pts)
2. What are the requirements for a discrete probability distribution?
3. Explain what binomial probability distribution is.
Chapter 6
1. Explain what a continuous random variable is. List examples.
2. Explain some basic characteristics of Normal Distribution.
3. What is the standard Normal Distribution?
4. Explain the difference between a raw score (x value) and a standard
score(z value).
5. How to convert a raw score to a standard score; and how to convert a
standard score to a raw score? 6. Explain how to use Table 2 for each of the following intervals:
a) z < a
b) z > a
c) a < z < b
Here a and b are constant z units. b is larger than a Describe the strategies we mentioned in class for theses 3 cases
7. Explain what the Inverse Normal Distribution is. How would you
figure out whether a problem is Normal Distribution type or Inverse
Normal type?