Basic concepts Flashcards

1
Q

Why are statistical tests important?

A
  • Inherent in process of doing quantitative research

- Essential in designing research and interpreting results

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2
Q

What is a statistical test?

A
  • A procedure for addressing a problem with a specified sequence of steps
  • Relies on assumptions
  • Requires the formulation of a hypothesis
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3
Q

What is a hypothesis?

A

An initial idea of expected patterns

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4
Q

Null hypothesis

A

H0 - The default - always assumed to be correct

- There is no statistically significant relationship/pattern

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5
Q

Alternative hypothesis

A

H1 - There is a statistically significant relationship/pattern

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6
Q

What is a confidence level?

A
  • The probability that H1 is correct

- e.g. 99% or 95%

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7
Q

How does a table of critical values work?

A

If the output is greater than the critical value, you reject the null

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8
Q

Why do we ‘fail to reject’ the null instead of ‘accepting’ the alternative?

A

Leaves room to re-test and improve

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9
Q

The area under a distribution curve…

A

Represents the probability of an outcome in that range

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10
Q

What is significance level?

A

How likely it is that the results are due to chance/The probability that the null hypothesis is correct

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11
Q

When do we accept H1?

A

If the significance level is sufficiently low (usually 0.05 or 0.01)

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12
Q

When is the critical value determined?

A

Before the test is carried out

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13
Q

What is the population?

A

The whole body of individuals we’re interested in

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14
Q

What is the sample?

A

A collection of individuals drawn from a population

- two samples from the same population are expected to have the same characteristics

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15
Q

What is a sampling strategy?

A

A method applied to choose a sample from a population

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16
Q

What are the main requirements in a sample?

A
  • Large enough to ensure precision

- Careful consideration to avoid bias

17
Q

What is accuracy?

A

A measure of correctness - how close the results are to the true value. This requires the sample to be representative of the population and measurements to be correct.

18
Q

What is precision?

A

A measure of reproducibility - how well a result has been determined without reference to its closeness to the true value. This requires the sample to be large enough to compensate for variability within the population.

19
Q

What is bias?

A

Over or underrepresentation of a particular characteristic of a population.

20
Q

How might bias occur?

A
  • Results from subtle aspects in our sampling strategy
  • Depends on the target population
    (e. g. door knocking)
21
Q

What are the fundamentals of sampling?

A
  • Every individual in the population has equal and independent probability of being included in the sample
  • Inclusion of one individual does not affect the selection of another
22
Q

What is random sampling?

A
  • Random selection
  • Often by assigning labels to a population
  • e.g. random number generator
23
Q

What is systematic sampling?

A

Selecting every nth individual from a population

24
Q

Why might interviewing people ‘at random’ be problematic and how could it be improved?

A
  • Might be influenced by conscious/subconscious bias
  • We can’t test for or correct this so it is not acceptable for practice in academic studies
  • Sample the nth person passing by (systematic) - the order of individuals is assumed to be random (unlike choosing every nth house)
25
Q

What is assumed normal distribution?

A
  • We assume samples and populations are approximately normally distributed
  • This is where we would use parametric statistics
26
Q

Ardoyne Road, Belfast…

A

There are patterns to the houses in that area based on what religion you are – you will get very different results from different parts of that area so you could systematically sample all protestant, or all catholic houses.

27
Q

What is discrete data?

A
  • Can only take particular values
  • May potentially be an infinite number of those values, but each is distinct and there’s no grey area in between. - Can be numeric (like numbers of apples) but it can also be categorical (like red or blue, or male or female, or good or bad)
28
Q

What is continuous data?

A
  • Not restricted to defined separate values, but can occupy any value over a continuous range
  • Between any two continuous data values there may be an infinite number of others
  • Continuous data are always essentially numeric