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Research Methods > Quantitative > Flashcards

Quantitative Flashcards

1
Q

Quan

A

a deductive approach
theory testing
quan starts with a theory and test hypothesis

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2
Q

Hypothesis

A

an expected answer to our research question

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3
Q

Theory =

A

a reasoned and precise speculation about the answer to a research question

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4
Q

reliability

A

the consistency of a measure of a concept

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5
Q

concepts

A

labels of ideas or phenomena

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6
Q

Descriptive inferences

A

set of observations in order to understand a phenomena

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7
Q

Validity

A

data quality- refers to the truthfulness of a measure -

measuring what we think it is measuring

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8
Q

Reliable

A

data collection is reliable - could apply the same procedure at a different time and will get the same results

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9
Q

Casual relationship

A

Causality is the relation between an event and a second event, where the second event is understood as a consequence of the first

However finding a relationship doesn’t mean its casual

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10
Q

Methodology

A
  • a system of methods used to test hypothesis

- steps to test a hypothesis

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11
Q

Measurement

A

process by which raw data is turned into numbers

imposing a numerical structure on our data

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12
Q

Coding

A

process which observations recorded in the course of social research - then transformed from raw data into categories and classifications which then become subject to quan data analysis

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13
Q

coding involves the act of measurement

A

trying to measure the underlying social variable

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14
Q

variables

A

measures of indicators
variables are how we operationalise social concepts
variable is a characteristic that is likely to vary

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15
Q

Not all variables are equal - need different levels

A

Nominal
Ordinal
Interval

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16
Q

Nominal level variables

A

are categorical

response categories cannot be placed in a specific order - can’t judge distance between

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17
Q

Nominal and Ordinal

A

both categorical

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18
Q

Examples of Nominal level variables

A

Sex

Ethnicity

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19
Q

Examples of Ordinal

A

Likert scale - agree, strongly agree

20
Q

Examples of Interval (continuous)

A

age

temperature

21
Q

Ordinal level variables -

A

can be placed in rank orders, one is greater than the other.
But do not have mathematically distance between

22
Q

Interval (scale) level variables (continuous) =

A

rank order, with uniformed distance between each response which allows for mathematically measurement

23
Q

Interval level variable is..

A

Continuous

24
Q

Missing data =

A

-99

25
Q

Each row in SPSS =

A

a case

26
Q

Each column in SPSS =

A

represents a variable

27
Q

Each cell in SPSS =

A

contains a response

28
Q

Visualising Nominal data -

A

Pie charts

interested in proportion of people

29
Q

Visualising Ordinal data-

A

Bar chart

compare proportion of people agreeing or disagreeing

30
Q

Visualising Interval (scale) data-

A

Histograms - normal distribution

31
Q

Histograms show is variables are..

A

Normall distributed

32
Q

Visualising relationship between 2 Interval (scale) variables =

A

Scatterplot

33
Q

Inference

A

using facts we know the data to learn about the facts we do not know

34
Q

Descriptive statistics

A

is the main tool to make descriptive inferences
allow us to describe our data
describe basic features of the sample we are interested in
- NOT looking for relationship
- patterns and trends!

35
Q

Characteristics of a variable - 3

A

distribution/frequency
central tendency
dispersion

36
Q

Characteristics of a variable shown in -

Frequency table

A

displays number of times that a value appears within the data set

37
Q

Characteristics of a variable shown in -

central tendency

A

includes the mean, median and mode values

they show us how clustered the data is

38
Q

Characteristics of a variable shown in -

Dispersion

A

Range and standard deviation

how spread out the data is

39
Q

Mode- can be used to describe -

A

nominal, ordinal and interval (scale)

value occurs most frequently

40
Q

Median - can be used to describe -

A

the middle in ordered data

ordinal and interval (scale)

41
Q

Mean - can be used to describe -

A

ONLY interval (scale)

42
Q

Bivariate Data

A

Data for two variables

shown in scatterplot

43
Q

Range =

A

measures between highest and lowest

large range may reveal outliers

44
Q

standard deviation =

A

measures the distance (deviation) of each value from the mean

45
Q

Range and standard deviation- can be used to describe -

A

interval (scale) (continuous)

Research Methods (11 decks)

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