Quantitative Research Methods

1
Quantitative Research Methods

• Excerpts from Hinkle, D. E., Wiersma, W., and
  Jurs, S. G. (2003) Applied Statistics for the
  Behavioral Sciences. Boston, MA Houghton Mifflin
  Company.

2
Statistics are a collection of

• theory and
• methods applied for the purpose of understanding
  data. (p.2)

3
The Summation Operator?
One very important mathematical operator used in
statistics is the summation operator, which is
used to simplify statistical formulas. It is
denoted by the Greek capital letter sigma
(?)which stands for the sum of. (p.3)
4
Order of Operations(PEMDAS)

• Parentheses (or brackets or braces)
• Exponents (e.g., squares or roots
• Multiplications
• Divisions
• Additions
• Subtractions (pp. 5-6)

5
Constant

• A constant is a characteristic that assumes
  the same value for all members of a group under
  study.
• (p. 7)

6
Variable

• A variable is a characteristic that can take
  on different values for different members of a
  group being studied. (p. 7)

7
Independent Variables

• Independent variables are either manipulated or
  classifying variables. In a medical study to
  determine the effect of a dosage of pills, the
  dosage is the manipulated variable, whereas
  gender may be a classifying variable. (pp. 7-8)

8
Dependent Variables

• Dependent variables are measures of the effect
  of the independent variables. (p. 8)

9
Measurement

• Measurement is a process of assigning numbers to
  characteristics according to a definite rule.
  Clearly not all measurement is the same. Some
  measurements are more precise than others. If we
  say an individual is tall, that is not as precise
  as saying that the person is six feet, seven
  inches. Some characteristics are more amenable to
  precise measurement than others. Given an
  accurate bathroom scale, we can measure an
  individuals weight very precisely. But it is
  more difficult to measure anxiety level or
  opinions precisely. (p. 8)

10
Scales of MeasurementFour Levels (from lowest to
highest)

• Nominal scale (categorizes without ordering the
  categories)
• Ordinal scale (categorizes and orders the
  categories)
• Interval scale (categorizes, orders, and
  establishes an equal unit in the scale)
• Ratio scale (categorizes, orders, establishes an
  equal unit, and contains a true zero point)
• (p. 11)

11
Qualitative Variables

• Variables measured on the nominal or ordinal
  scales are often referred to as qualitative
  variables because the measurement consists of
  unordered or ordered (ranked) discrete
  categories, such as religious backgrounds or
  grades.

12
Quantitative Variables

• Variables measured on the interval or ratio
  scales are quantitative variables. It is assumed
  that quantitative variables have underlying
  continuity that is, they can take on any value
  on the measurement scale. Height, weight,
  temperature, and IQ are examples of quantitative,
  continuous variables. (p. 11)

13
A Population

• A population includes all members of a defined
  group (e.g., all full-time employees of a given
  organization at a specific time all residents of
  NYC at a specific time)
• Parameters are descriptive measures of a
  population. (p.12)

14
A Sample

• A Sample is a subset of a population.
• Statistics are descriptive measures of a sample.
  (p. 12)

15
Descriptive Statistics

• Descriptive Statistics is a collection of
  methods for
• classifying and
• summarizing numerical data.

16
Inferential Statistics

• Inferential statistics is a collection of
  methods for making inferences about the
  characteristics of the population from knowledge
  of the corresponding characteristics of the
  sample. (p. 13)