Introduction to quantitative methods Flashcards

1
Q

What does quantitative research involve?

A
• Involves a systematic examination
of phenomena through;
• Testing a hypothesis
• Development of statistical models to explain observable phenomena
• Nomothetic (generalizability)
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2
Q

What types of quantitative research questions are there?

A
  • Descriptive
  • Comparative
  • Relationship/Causal
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3
Q

Explain a descriptive quantitative research question?

A
  • Wanting to understand a situation, facts
  • When you want to describe what is going on or what exists
  • Non intervention
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4
Q

Explain a comparative quantitative research question?

A

• Two or more things are compared in the
aim of finding something about one or all
of them
e.g.How common is racial abuse experienced by
professional footballers compared to professional rugby union players?

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5
Q

Explain a relationship/causal quantitative research question?

A

• Relationships or the causal associations between variables
• Understand nature of and relationships between variables
• Most relevant when thinking about interventions
e.g. Do air pollution levels change fan attendance
at Chinese football matches?

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6
Q

What is quantitaive research?

A

Quantitative Research focuses on the collection and

application of statistics

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7
Q

What is the research process?

A
  1. Specify clearly a question of interest
  2. Design a suitable means of gathering data
  3. Collect data in unambiguous and organised manner
  4. Plot or tabulate data in an appropriate form
  5. Build a statistical model
  6. Analyse data using this model
  7. Report, in simple English, the answers and use graphs where appropriate to ease interpretation
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8
Q

What are statistics?

A

Science that involves collecting, summarising,

analysing and interpreting data.

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9
Q

What is a statistic and why are they used when undertaking research?

A

A single number summarising a variable of interest
Why do we undertake research using statistics?
• To test a hypothesis
• Are the results real?
• Do the results matter?

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10
Q

What is data?

A

Collection of facts or information

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11
Q

What are variables of interest?

A

What is being observed or measured?

•A characteristic associated with a group being studied

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12
Q

What are the two types of variables of interest?

A
Explanatory variable (Independent): What are you 
manipulating/ what you think is associated with outcome
• Response variable (Dependent): Outcome variable
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13
Q

What is hypothesis testing?

A

• Hypothesis testing is a statistical method that is used in
making statistical decisions using experimental data.

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14
Q

What are the two types of hypothesis?

A
  • the null hypothesis is a general statement or default position that there is no relationship between two measured phenomena, or no association among group
  • A position that states something is happening, a new theory is true instead of an old one
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15
Q

What is a population?

A

• A total set of observations that can be made

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16
Q

What is a parameter?

A

A single number that summarises a variable of interest

17
Q

What are the qaulitative data forms?

A

• Categorical (Nominal )-Named categories (non
numeric) no order
• Ordered categorical (Ordinal)-Categories with a natural order, i.e 1st, 2nd, 3rd

18
Q

What are the quantitative data forms?

A
  • Discrete (interval)

* Continuous ( Ratio)

19
Q

What is discrete data?

A
• Integer values (whole 
numbers)
• Eg. Time of day
• Temperature
• No meaningful zero value
• Cannot multiply and divide
20
Q

What is continuous data?

A
  • Variables can take any value and starts at zero
  • Eg. height, BMI, age, crowd size
  • Meaningful zero value
  • Can multiply and divide
21
Q

Why does data type matter?

A
  • Drives the research process
  • Should be considered from the moment research question is determined
  • Generally continuous outcomes need smaller samples
  • Must be appropriate to answer the research question
  • Guides the statistical analytic method
22
Q

What types of reliability are there?

A
  • Stability-will results be the same
  • Internal Reliability- measures whether several items that propose to measure the same general construct produce similar scores e.g. correct calibration of scales
  • Inter‐Observer Consistency- extent to which two or more observers are observing and recording behaviour in the same way
23
Q

What are the two types of validity of measurement?

A

•Internal validity:
the extent to which a study establishes a trustworthy cause-and-effect relationship between a treatment and an outcome
Manipulation or other causes (variables)?

• External validity:
applying the conclusions of a scientific study outside the context of that stud
Generalisability to a wider population?
Comparability with other literature