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Quantitative Methods in Media and Communication Summary

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Erasmus Universiteit Rotterdam (EUR)

This summary encompasses course material from lectures, tutorials, cases brought from class activities and assignments as well as further elaborations on everything taught in the course. Besides its theoretical nature, this summary also includes practical cases such as course cases and examples of ...

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Type Samenvatting

statistics
thesis
quantitative
communication
anova
t test
factor analysis
2nd year
eur
quantitative methods in media and communication
erasmus university rotterdam

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Victoria Sinner

QUANTITATIVE METHODS – EXAM NOTES

Theoretical aspect:

- Theory: an interrelated set of variables formed into hypotheses that specify the relationship
among variables, with the purpose of explaining natural phenomenon.
- Theoretical rationale: provides an explanation or prediction about why and how variable X
(independent variable) would influence variable Y (dependent variable).
- Variable: a characteristic or attribute that varies among the people that are being studied.
- Hypotheses: tested with statistics whereas opinions are not, can be answered by TRUE or
FALSE, and are followed up by data.
o Two types of hypotheses:
▪ Null hypothesis (H0):
• No difference nor change.
• Never stated, always implied.
▪ Alternative hypothesis (H1):
• Statement of prediction.
• Actual research hypothesis.
o Goal is to accept one and reject the other.
• Can either be directional (going in a particular direction) or non-
directional.
- Spurious relationship is a relationship in which the IV and DV seem related but in fact are
not.
o Ex. Age of miss American and murders by steam.
- Confounding variables are variables that are not measured but might influence or explain the
observed relationship.
o Ex. Direct relationship between the number of chimneys and number of pregnant
women.
▪ The confounding variable is the number of citizens: the more citizens, the
more houses (and chimney’s) and the more pregnant women within a
community.
▪ The IV and DV are related through a 3rd variable that links them.
- Moderating variable (ex. Gender) affect the relationship between the IV and the DV, such that
the effect may be present for one group (males) and not for another (females).
o Moderation variables tell you for whom an IV affects the DV.
- Control variables are a special type of IV that research measure because they potentially
influence the DV – but not for certain.
- Intervening/mediating variables stand between the IV and DV and mediate the effects of the
IV on the DV.
o Mediating variables tell you how an IV affects the DV.

1

, Victoria Sinner

Operationalization, reliability, and validity:
- Operationalization → the process of defining or selecting the correct measurement of your
study. Quality of results depends on quality of measurements.
o The better the scales the better results you will obtain.
How to define measurements?
- You will make use of variables; these may be abstract:
o Press freedom, materialism, life satisfaction, life quality.
o These abstract concepts cannot be measured with one question.
o Characteristics like gender, educational level, nationality can be asked with one
simple question.
- To measure abstract concepts, we generally use a set of questions → scales.
o Scales contain multiple items, being questions or statements, which participants must
react to.
o For each item of a scale, an identical number of answer options should be provided.
o Scale scores can be calculated in two ways:
1. The scores on the separate items (questions/statements) can be summed or
averaged.
a. Summing the scores allows the categorization of the participant:
intelligence, autism, addiction, total number of hours spend on social
media.
b. Averaging the scores allows the interpretation of the scale with the
original answer option.
2. ..
o Some scales combine so-called positive and negative items. In such cases, the
negative items need to be recoded before the scale score is calculated.
▪ Statements arguing for low or high level of (…). One statement might argue
for a high level and the next for a low level, but the answer options remain
the same so in order to prevent them from contradicting or balancing each
other out we need to recode.
• If scores are (strongly disagree) 1-7 (strongly agree), when reverse
coding: 1=7, 2=6, 3=5 etc.
• Final score is calculated by determining the average of original and
recoded scores.
- What are the criteria for a good operationalization:
o You need to have a reliable measure and should always measure the same.
o You need valid measures; did it actually measure what you wanted it to?
o You need an objective measure; does it measure the same way irrespective of who
answers?
▪ Important to assess the scales internal consistency and content validity.

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