Quantitative methods of communication research
Gert-Jan De Bruijn
good to know
- examen = open vragen en MC (11/20)
- ook 3 individuele taken (allemaal op 3/20)
- case assignments
- spss downloaden
1
,LES 1 - 26/09
QUANTITATIVE METHODS
➔ deals with methods/data which you can quantify: putting things into numbers
➔ assumption is that you can put everything in numbers
➔ descriptives
➔ how often something occurs?
◆ How much misinformation is present on Facebook?
◆ How many students filled in the survey I sent out?
➔ Associations
➔ how things are related?
◆ More misinformation leads to less governmental trust
◆ Attending more classes leads to better course grades
➔ Differences
➔ how things are different between groups or messages
◆ 80% chance that a fear appeal will make the public smoke less, when compared to a social
norm
◆ Do social robots OR chatbots at home lead to less loneliness?
Waarom cijfers gebruiken?
-> dagelijkse taal is super onprecies, cijfers geven een exactere en gedetailleerdere info
vb.: ‘its thursday evening’ tov ‘it’s thursday 25th of September 2025, 7pm’
-> quantitative research disagrees with this completely
measurement levels
1. nominal
2. ordinal
3. interval
4. ratio
NOMINAL
➔ the numbers have no meaning, it doesn’t change anything if u change the numbers
➔ Numbers are nothing more than labels assigned by the researcher(s) for categorization
➔ In other words, the numbers in categorical data do not have arithmetic or mathematical
value
➔ They can be altered without any impact on the results of the analysis
ORDINAL
➔ Numbers in ordinal data are labels assigned by the researcher(s) to denote the
importance of the ranking
2
,➔ 2 is bigger than 1, 3 is bigger than 2, there's a ranking
➔ In other words, the numbers in ordinal data have arithmetic value by denoting where they
rank / are in the order
➔ Ranking = relative
INTERVAL
➔ equal intervals between values
◆ In other words, the difference between 20 degrees & 30 degrees is the same as
between 40 degrees & 50 degrees in temperature
➔ important: a score of zero does not mean absence!
◆ Temperature of zero does not mean there is no temperature.
RATIO
➔ Numbers in ratio data indicate equal intervals between values
◆ In other words, the difference between 20 degrees & 30 degrees is the same as
between 40 degrees & 50 degrees in temperature
➔ However: a score of zero does mean absence.
◆ Watching zero minutes of TV is the same as watching no TV
➔ Most - but definitely not all - quantitative studies in communication science deal with
ordinal measures and/or nominal measures
➔ Why is the measurement level of importance?
◆ It dictates the type of analysis you can / should run
Ordinal | interval | ratio data: how to describe these data?
• Two main properties
• Central tendency
• Variability
• Three main measures of central tendency
1. Arithmetic mean | Average = sum of values/number of scores
2. Median = the middle value (when ranked from lowest to highest)
3. Mode = the most frequent value
3
, Four main measures of variability
1. Minimum and maximum values
2. Range: maximum value minus minimum
value
3. Interquartile range: 75% value minus 25%
value
4. Standard deviation: average of the average
deviation from mean score
4
Gert-Jan De Bruijn
good to know
- examen = open vragen en MC (11/20)
- ook 3 individuele taken (allemaal op 3/20)
- case assignments
- spss downloaden
1
,LES 1 - 26/09
QUANTITATIVE METHODS
➔ deals with methods/data which you can quantify: putting things into numbers
➔ assumption is that you can put everything in numbers
➔ descriptives
➔ how often something occurs?
◆ How much misinformation is present on Facebook?
◆ How many students filled in the survey I sent out?
➔ Associations
➔ how things are related?
◆ More misinformation leads to less governmental trust
◆ Attending more classes leads to better course grades
➔ Differences
➔ how things are different between groups or messages
◆ 80% chance that a fear appeal will make the public smoke less, when compared to a social
norm
◆ Do social robots OR chatbots at home lead to less loneliness?
Waarom cijfers gebruiken?
-> dagelijkse taal is super onprecies, cijfers geven een exactere en gedetailleerdere info
vb.: ‘its thursday evening’ tov ‘it’s thursday 25th of September 2025, 7pm’
-> quantitative research disagrees with this completely
measurement levels
1. nominal
2. ordinal
3. interval
4. ratio
NOMINAL
➔ the numbers have no meaning, it doesn’t change anything if u change the numbers
➔ Numbers are nothing more than labels assigned by the researcher(s) for categorization
➔ In other words, the numbers in categorical data do not have arithmetic or mathematical
value
➔ They can be altered without any impact on the results of the analysis
ORDINAL
➔ Numbers in ordinal data are labels assigned by the researcher(s) to denote the
importance of the ranking
2
,➔ 2 is bigger than 1, 3 is bigger than 2, there's a ranking
➔ In other words, the numbers in ordinal data have arithmetic value by denoting where they
rank / are in the order
➔ Ranking = relative
INTERVAL
➔ equal intervals between values
◆ In other words, the difference between 20 degrees & 30 degrees is the same as
between 40 degrees & 50 degrees in temperature
➔ important: a score of zero does not mean absence!
◆ Temperature of zero does not mean there is no temperature.
RATIO
➔ Numbers in ratio data indicate equal intervals between values
◆ In other words, the difference between 20 degrees & 30 degrees is the same as
between 40 degrees & 50 degrees in temperature
➔ However: a score of zero does mean absence.
◆ Watching zero minutes of TV is the same as watching no TV
➔ Most - but definitely not all - quantitative studies in communication science deal with
ordinal measures and/or nominal measures
➔ Why is the measurement level of importance?
◆ It dictates the type of analysis you can / should run
Ordinal | interval | ratio data: how to describe these data?
• Two main properties
• Central tendency
• Variability
• Three main measures of central tendency
1. Arithmetic mean | Average = sum of values/number of scores
2. Median = the middle value (when ranked from lowest to highest)
3. Mode = the most frequent value
3
, Four main measures of variability
1. Minimum and maximum values
2. Range: maximum value minus minimum
value
3. Interquartile range: 75% value minus 25%
value
4. Standard deviation: average of the average
deviation from mean score
4
