Quantitative Methods in Media & Communication
CM2005
Course material: SPSS survival manual, 6th edition, Julie Pallant
This summary includes:
Lectures
Written by: Esmée Lieuw On
ESMEE LIEUW ON 1
, Lecture 1: RQs, Hypotheses, Variables
Qualitative methods are… Quantitative methods are…
Interpretative, deep, nuanced Deductive, generalizable, evidence-based
Fluffy, pretentious, feely Rigid, meaningless, numbers 5-based ever
→ Both methods need each other to come to conclusions!
The General Use of Theory
• Theory = an interrelated set of variables formed into hypotheses that specify the
relationship among variables, with the purpose of explaining natural phenomenon
• Variable = A characteristic or attribute that varies among the people that are being
studied
o Independent variables (IV) = those that probably influence/affect outcomes
[treatment, manipulated, antecedent, predictor]
o Dependent variables (DV) = those that are the presumed result of the
influence of the IV [criterion, outcome, effect]
Qualitative RQs Quantitative RQs
Aim To discover To test (hypotheses)
To seek to understand To examine relationship
variables
To explore To compare
To describe To describe
Type Open questions More narrow questions
Examples How… To what extent…
What is meaning… What effect…
… causes…
Hypotheses Versus Opinions
• Hypotheses are tested with statistics, opinions are not
• Hypotheses can be answered by saying TRUE/FALSE
• Hypotheses are followed up by data
• Two types of hypotheses:
1. Null hypothesis (H0)
o Assumes no difference or change
o Never stated, always implied
2. Alternative hypothesis (H1)
o Statement of prediction
o Actual research hypothesis
• The goal of hypothesis testing is to reject one hypothesis and accept the other
• Type of H1 hypotheses:
ESMEE LIEUW ON 2
, o Directional hypothesis
▪ Difference or effect in particular direction
▪ E.g. media violence increases mood
o Nondirectional hypothesis
▪ Difference or effect but not in particular direction
▪ Avoid when possible
▪ E.g. media violence influences mood
Variables That Influence the Relationship of IV and DV
• A spurious relationship is a relationship in which the IV and DV seem related, but
are in fact not
• Confounding variables are variables that are not measured but might influence or
explain the observed relationship (ex. More chimneys = more pregnant women,
confounding variable is number of citizens → more citizens, more houses (and
chimneys!) and the more pregnant women)
• According to Creswell, spurious and confounding relationships are the same. This is
NOT true.
o In spurious relationships, IV and DV are completely unrelated.
o In confounding relationships, IV and DV are related through a third variable
that links them.
• Control variables are a special type of independent variable that researchers measure
because they potentially influence the dependent variable (usually demographics such
as age)
• Intervening/mediating variables stand between the independent and dependent
variables, and ‘mediate’ the effects of the IV on the DV
o Mediating variables tell you how an independent variable affects the
dependent variable
• Moderating variables (e.g. gender) affect the relationship between the IV and DV,
such that the effect may be present for one group (i.e., males) but not another (i.e.,
females)
o Moderating variables tell you for whom an independent variable affects the
dependent variable
ESMEE LIEUW ON 3
CM2005
Course material: SPSS survival manual, 6th edition, Julie Pallant
This summary includes:
Lectures
Written by: Esmée Lieuw On
ESMEE LIEUW ON 1
, Lecture 1: RQs, Hypotheses, Variables
Qualitative methods are… Quantitative methods are…
Interpretative, deep, nuanced Deductive, generalizable, evidence-based
Fluffy, pretentious, feely Rigid, meaningless, numbers 5-based ever
→ Both methods need each other to come to conclusions!
The General Use of Theory
• Theory = an interrelated set of variables formed into hypotheses that specify the
relationship among variables, with the purpose of explaining natural phenomenon
• Variable = A characteristic or attribute that varies among the people that are being
studied
o Independent variables (IV) = those that probably influence/affect outcomes
[treatment, manipulated, antecedent, predictor]
o Dependent variables (DV) = those that are the presumed result of the
influence of the IV [criterion, outcome, effect]
Qualitative RQs Quantitative RQs
Aim To discover To test (hypotheses)
To seek to understand To examine relationship
variables
To explore To compare
To describe To describe
Type Open questions More narrow questions
Examples How… To what extent…
What is meaning… What effect…
… causes…
Hypotheses Versus Opinions
• Hypotheses are tested with statistics, opinions are not
• Hypotheses can be answered by saying TRUE/FALSE
• Hypotheses are followed up by data
• Two types of hypotheses:
1. Null hypothesis (H0)
o Assumes no difference or change
o Never stated, always implied
2. Alternative hypothesis (H1)
o Statement of prediction
o Actual research hypothesis
• The goal of hypothesis testing is to reject one hypothesis and accept the other
• Type of H1 hypotheses:
ESMEE LIEUW ON 2
, o Directional hypothesis
▪ Difference or effect in particular direction
▪ E.g. media violence increases mood
o Nondirectional hypothesis
▪ Difference or effect but not in particular direction
▪ Avoid when possible
▪ E.g. media violence influences mood
Variables That Influence the Relationship of IV and DV
• A spurious relationship is a relationship in which the IV and DV seem related, but
are in fact not
• Confounding variables are variables that are not measured but might influence or
explain the observed relationship (ex. More chimneys = more pregnant women,
confounding variable is number of citizens → more citizens, more houses (and
chimneys!) and the more pregnant women)
• According to Creswell, spurious and confounding relationships are the same. This is
NOT true.
o In spurious relationships, IV and DV are completely unrelated.
o In confounding relationships, IV and DV are related through a third variable
that links them.
• Control variables are a special type of independent variable that researchers measure
because they potentially influence the dependent variable (usually demographics such
as age)
• Intervening/mediating variables stand between the independent and dependent
variables, and ‘mediate’ the effects of the IV on the DV
o Mediating variables tell you how an independent variable affects the
dependent variable
• Moderating variables (e.g. gender) affect the relationship between the IV and DV,
such that the effect may be present for one group (i.e., males) but not another (i.e.,
females)
o Moderating variables tell you for whom an independent variable affects the
dependent variable
ESMEE LIEUW ON 3
