Types of Data Flashcards
Quantitative Data
Numerical data
eg reaction time or number of wins
One Strength of Quantitative Data
+ Easier to analyse. Can draw graphs and calculate averages. Can eyeball data and see patterns at a glance
One Limitation of Quantitative Data
- Oversimplifies behaviour. eg using rating scale to express feelings. Means that individual meanings are lost
Qualitative Data
Non-numerical data expressed in words
eg extract from a diary
One Strength of Qualitative Data
+ Represents complexities. More detail included (such as explaining your feelings). Can also include information that is unexpected
One Limitation of Qualitative Data
- Less easy to analyse. Large amount of detail is difficult to summarise. Therefore, it is difficult to draw conclusions
Primary Data
First hand data collected for the purpose of the investigation
One Strength of Primary Data
+ Fits the job. Study designed to extract only the data needed. Information is directly relevant to research aims
One Limitation of Primary Data
- Requires time and effort. Design may involve planning and preparation. Secondary data can be accessed within minutes
Secondary Data
Collected by someone other than the person who is conducting the research
(eg taken from books, journals, articles etc)
One Strength of Secondary Data
+ Inexpensive. The desired information may already exist. Therefore, requires minimal effort making it inexpensive
One Limitation of Secondary Data
- Quality may be poor. Information may be outdated or incomplete. Therefore, challenges the validity of the conclusions
Meta-Analysis
A type of secondary data that involves combining data from a large number of studies.
Calculation of effect size
One Strength of Meta-Analysis
+ Increases validity of conclusions. The eventual sample size is much larger than individual samples. Therefore, increases the extent to which generalisations can be made
One Limitation of Meta-Analysis
- Publication bias. Researchers may not select all relevant studies, leaving out negative or non-significant results. Data may be biased because it only represents some of the data and incorrect conclusions are drawn
Mean
Arithmetic average.
Add up all the scores and divide by the number of socres
One Strength of the Mean
+ Sensitive. Includes all the scores in the data set within the calculation. Therefore, more of an overall impression of the average than median or mode
One Limitation of the Mean
- May be unrepresentative. One very large or small number makes it distorted. The median or mode tend not to be so easily distorted
Median
Middle value.
Place scores in ascending order and select middle value if there are two values in the middle, the mean of these is calculated
One Strength of the Median
+ Unaffected by extreme scores. The median is only focused on the middle value. Therefore, it may be more representative of the data set as a whole
One Limitation of the Median
- Less sensitive than the mean. Not all scores are included in the calculation of the median. Therefore, extreme values may be important
Mode
Most frequent or common value.
Used with categorical/nominal data
One Strength of the Mode
+ Relevant to categorical data. When the data is discrete (ie represented in categories). Sometimes, the mode is the only appropriate measure
One Limitation of the Mode
- An overly simple measure. There may be many modes in a data set. It is not a useful way of describing data when there are many modes
