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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

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. (4pts)

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 ;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 and x . How do you determine which is appropriate to use in a problem?

3. Explain the difference between and s. How do you determine which is appropriate to use in a problem?

4. What is the relationship between variance and standard deviation?

(2pts)

5. Explain the difference between range and interquartile range. (4pts)

6. Explain what the coefficient of variation is. What is the advantage of

using it compared to standard deviation? (4pts)

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.

2. What are the requirements for a discrete probability distribution?

3. Explain what binomial probability distribution is. Hint: list requirements in slides.

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 (less than)

b) z > a (more than)

c) a < z < b (between)

Here a and b are constant z units. b is larger than a

Describe the strategies we mentioned in class for theses 3 cases (6pts)

7. Explain what the Inverse Normal Distribution is. How would you figure out whether a problem is Normal Distribution type or InverseNormal type?

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