Week 5-7 Flashcards

1
Q

Give an example: Nominal level of measurement

A

Ethnic group- Chinese

Gender- male, female

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2
Q

Give an example: Ordinal level of measurement

A

University grades- pass, credit, D, HD

T-shirts- S, M, L, XL

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3
Q

Give an example: Interval/Discrete level of measurement

A

IQ scores

Temperature

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4
Q

Give an example: Ratio/Continuous level of measurement

A

Height

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5
Q

Give an example: Categorical Data

A

Nominal and Ordinal

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6
Q

Give an example: Continuous data

A

Interval and Ratio

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7
Q

Explain: Nominal level of measurement

A

classifies objects or events into discrete categories not measured or ordered

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8
Q

Explain: Ordinal level of measurement

A

shows relative ranking of objects or events in hierarchical order

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9
Q

Explain: Interval/ Discrete level of measurement

A

differences between scores or measures treated as equal—zero is arbitrary

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10
Q

Explain: Ratio/Continuous level of measurement

A

shows ranking of events or objects on scales with equal intervals and absolute zero; the zero point makes the ratio of scale values meaningful

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11
Q

Descriptive Results/Statistics

Name the 3 ways data is described?

A

1) By measures of central tendency (mean, mode, median)
2) By measures of dispersion (variabiltiy)
3) By measures of association (frequency)

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12
Q

What are the 3 measures of Central Tendency?

A

Mean- average
Median- middle score (divided scores are equal halves)
Mode- score that occurs the most

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13
Q

Define: Statistics

A

are a way of organising and making sense of data obtained by measurement

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14
Q

Explain: Descriptive Statistics

A

allow us to describe our sample in a comprehensive way without drawing any statistical inferences from the data

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15
Q

Explain: Inferential Statistics

A

Provides procedures to draw inferences about a population from a sample
e.g. deciding whether the data collected shows differences and patterns (parametric and non parametric)

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16
Q

Define: Measures of Central Tendency

A

A single central score that can be used to describe the centre of a distribution of scores

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17
Q

Define: Variability (dispersion)

A

is concerned with the spread of the data

Common measures are

  • Range
  • Variance
  • Standard deviation
18
Q

Measures of Variability

Define: Range

A

simplest and most unstable measure of variability

19
Q

Measures of Variability

Define: Variance

A

permits mathematical manipulation of different scores and includes every score in the distribution

20
Q

Measures of Variability

Define: Standard Deviation

A

the most frequently used measure based on the concept of the normal curve

21
Q

Explain: Inferential statistics

A

Inferential statistics enable inferences and conclusions to be drawn from the data

  • is based on probability theory and permits the generalisation from a specific sample, or samples, to the entire population
22
Q

If research results are Inferential, the results are about what 2 types of significance?

A

Statistical significance

Clinical significance

23
Q

Define: p-value

A

probability due to chance
p=0.05

  • In simpler terms if p<0.05 there is a 95% chance that the result was due to the experiment OR alternately, there is a 5% chance that it was merely coincidence.
24
Q

What is the common measure of variability used for estimation?

A

the Confidence Interval

25
Q

Explain: Confidence interval

A

CI gives the range in which the true value is likely to be

  • the 95% suggests the degree of certainty of the estimation
26
Q

What is Clinical Significance?

A

is when the treatment effect (confidence interval) is equal or more than the MID (minimal important difference)

27
Q

Qualitative Research

Explain: Phenomenology

A

Focuses on peoples lived experiences (their interpretations and understanding in their everyday life)
- Can be descriptive and interpretive

28
Q

Qualitative Research Designs

Explain: Ethnography

A

Is the study of cultures and subcultures

- the beliefs, values, language and attitudes that influence the behaviour patterns of a specific group of people

29
Q

Qualitative Research Design

What are the features of Ethnography

A

Focuses on group behaviours, interactions and art if acts

- uses a variety of data sources but must inc. interview and participant observation- fieldwork

30
Q

Qualitative Research Design

Explain: Grounded Theory

A

Often used when the topic is about change or nature of findings are unclear

  • flexible and exploratory
  • generates questions along the way
31
Q

Quantitative Research

What are the 4 types Non-probability Sampling

A

Convenience sampling
Purposive sampling
Snowball sampling
Theoretical sampling

32
Q

Quantitative Research- Non-probability sampling

Explain: Convenience sampling

A

Participants are chosen for ease of access (because its convenient)

33
Q

Quantitative Research- Non-probability sampling

Explain: Purposive sampling

A

Participants are chosen because of relevance to the research question

34
Q

Quantitative Research- Non-probability sampling

Explain: Snowball sampling

A

This relies on participant referrals

35
Q

Quantitative Research- Non-probability sampling

Explain: Theoretical sampling

A

Used for theory and concept development

36
Q

What is the rule of thumb for sample sizes in the various Qualitative studies

A

Biography/case study- 1 person/case
Phenomenology- 10-15 people
Grounded theory/ethnography- 20-30 people
Focus groups- 5-10 people in each group

37
Q

Define: Statistical power

A

refers to whether the sample size is large enough to detect a treatment effect

38
Q

Define: Likert scale

A

is an exmaple of a fixed response format used to determine participants attitude or opinion.
Eg. questionnaire with answers as statement so agree to disagree

39
Q

Explain: T-test

A

independent groups t-test tests for differences in mean outcome between two mutually exclusive groups

40
Q

Explain: Chi-square

A

is a non-parametric statistic that is used to determine whether the frequency in each category under study is different from what would be expected if there was no association between the categories

41
Q

Define: Data saturation

A

The point at which data collection ceases, and you do not have any more new information, information gathered has become repetitive.

42
Q

What is the 4 criteria for assessing the trustworthiness of Qualitative studies

A

Credibility- truth of findings
Auditability- accountability as judged by the adequacy of information
Fittingness- faithfulness to everyday reallity of the participants
Confirmability- findings that reflect implementation of all 3 criteria