Descriptive statistics Flashcards
nominal data
results are shown in 2 or more categories
shows number of times something occurred
no scores for individual participants
ordinal data
individual scores for each participant
results can be placed in rank order
interval data
made up from a scientific scale
individual score for each participant
can go into negatives
e.g temperature
ratio data
made up from a scientific scale
individual score for each participant
cant go into negatives - absolute zero
mathematical units
e.g weight, distance, time
strength of nominal data
easy to analyse
strength of ordinal data
allows for some comparison between participants, can rank them
data can be simplified and treated as nominal
strength of interval and ratio data
provides measurement of participants in universally accepted measurements
allows for detailed comparison
data can be simplified and treated as ordinal or nominal
weakness of nominal data
does not allow for comparisons between participants
weakness of ordinal data
data doesn’t always allow us to see difference between participants’ scores only that someone has scored better/worse
not measured in scientific units
weakness of interval and ratio data
no weaknesses
strength of mean and is it CT or D
CT - uses all raw data so representative
strength of median and is it CT or D
CT - not affected by extreme scores
strength of mode and is it CT or D
CT - not influenced by extreme scores and can show most popular value
weakness of mean
misreading as affected by extreme scores
weakness of median
can be distorted by small sample sizes
weakness of mode
does not use all the data so may not be representative
strength of range and is it CT or D
D - easy to calculate
strength of variance and is it CT or D
D - takes every score into account and is therefore not affected by outliers
strength of SD and is it CT or D
D - more in line with the original set of data
weakness of range
can be influenced by extreme scores
can be misleading as it tells us nothing about the distribution of the other scores
weakness of variance
data is not in line with the original set of data
weakness of SD
requires a more complex calculation
steps of SD calculation (7)
- add up number of scores to give you n
- calculate the mean
- calculate difference between individual score and the mean score
- square the difference
- sum the square roots
- divide the sum of squares by n
- root the variance
3 types of bar chart
bar chart, stacked bar chart, paired bar chart
strength of quantitative data
allows for easy comparison between groups so can draw valid conclusions
strength of qualitative data
gain insight into behavior, may learn why people behaved the way they did
weakness of quantitative data
limited insight into data
know what happened but don’t know why
weakness of qualitative data
harder to compare between groups and participants
prone to bias, subjective
primary data
data collected directly by the researcher through a study
secondary data
data obtained by other people
strength of primary data
researcher in control so can ensure that the data is collected properly like standardized instructions - more faith invalidity of findings
weakness of primary data
data does not already exist so the researcher would need to plan a suitable and ethical procedure for data collection which takes time
strength of secondary data
data already exists so it can be accessed without the need to plan and carry out suitable research
weakness of secondary data
quality of the data will be subject to any weaknesses present in the original design so validity in findings may be questionable
which tables record raw data
frequency tables and tally charts
