Quantitative

Question 1

Quan

Answer 1

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

Question 2

Hypothesis

Answer 2

an expected answer to our research question

Question 3

Theory =

Answer 3

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

Question 4

reliability

Answer 4

the consistency of a measure of a concept

Question 5

concepts

Answer 5

labels of ideas or phenomena

Question 6

Descriptive inferences

Answer 6

set of observations in order to understand a phenomena

Question 7

Validity

Answer 7

data quality- refers to the truthfulness of a measure -

measuring what we think it is measuring

Question 8

Reliable

Answer 8

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

Question 9

Casual relationship

Answer 9

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

Question 10

Methodology

Answer 10

• a system of methods used to test hypothesis

- steps to test a hypothesis

Question 11

Measurement

Answer 11

process by which raw data is turned into numbers

imposing a numerical structure on our data

Question 12

Coding

Answer 12

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

Question 13

coding involves the act of measurement

Answer 13

trying to measure the underlying social variable

Question 14

variables

Answer 14

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

Question 15

Not all variables are equal - need different levels

Answer 15

Nominal
Ordinal
Interval

Question 16

Nominal level variables

Answer 16

are categorical

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

Question 17

Nominal and Ordinal

Answer 17

both categorical

Question 18

Examples of Nominal level variables

Answer 18

Sex

Ethnicity

Question 19

Examples of Ordinal

Answer 19

Likert scale - agree, strongly agree

Question 20

Examples of Interval (continuous)

Answer 20

age

temperature

Question 21

Ordinal level variables -

Answer 21

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

Question 22

Interval (scale) level variables (continuous) =

Answer 22

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

Question 23

Interval level variable is..

Answer 23

Continuous

Question 24

Missing data =

Answer 24

-99

Question 25

Each row in SPSS =

Answer 25

a case

Question 26

Each column in SPSS =

Answer 26

represents a variable

Question 27

Each cell in SPSS =

Answer 27

contains a response

Question 28

Visualising Nominal data -

Answer 28

Pie charts | interested in proportion of people

Question 29

Visualising Ordinal data-

Answer 29

Bar chart | compare proportion of people agreeing or disagreeing

Question 30

Visualising Interval (scale) data-

Answer 30

Histograms - normal distribution

Question 31

Histograms show is variables are..

Answer 31

Normall distributed

Question 32

Visualising relationship between 2 Interval (scale) variables =

Answer 32

Scatterplot

Question 33

Inference

Answer 33

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

Question 34

Descriptive statistics

Answer 34

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!

Question 35

Characteristics of a variable - 3

Answer 35

distribution/frequency central tendency dispersion

Question 36

Characteristics of a variable shown in - | Frequency table

Answer 36

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

Question 37

Characteristics of a variable shown in - | central tendency

Answer 37

includes the mean, median and mode values | they show us how clustered the data is

Question 38

Characteristics of a variable shown in - | Dispersion

Answer 38

Range and standard deviation | how spread out the data is

Question 39

Mode- can be used to describe -

Answer 39

nominal, ordinal and interval (scale) | value occurs most frequently

Question 40

Median - can be used to describe -

Answer 40

the middle in ordered data | ordinal and interval (scale)

Question 41

Mean - can be used to describe -

Answer 41

ONLY interval (scale)

Question 42

Bivariate Data

Answer 42

Data for two variables | shown in scatterplot

Question 43

Range =

Answer 43

measures between highest and lowest | large range may reveal outliers

Question 44

standard deviation =

Answer 44

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

Question 45

Range and standard deviation- can be used to describe -

Answer 45

interval (scale) (continuous)