Data Handling And Analysis Flashcards
Quantitive data
Numerical data
Quantitive data advantages
Easier to analyse
can draw graphs and calculate averages, can eyeball data and see patterns at a glance
Quantitive data disadvantages
Oversimplifies behaviour
e.g. using a rating scale to express feelings
Means individual meaning may be lost
Qualitative data
Non-numerical data expressed in words
Qualitative data advantages
Represents complexities
More detail included (e.g. explaining your feelings)
Can include unexpected information
Qualitative data disadvantage
Less easy to analyse
Large amount of detail is difficult to summarise
Difficult to draw upon conclusions 
Primary data
First-hand data collected for the purpose of the investigation
Primary data advantage
Fits the job
The Studys designed to extract only the data needed
Information is directly relevant to the researchers aims 
Primary data disadvantage
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 research research e.g. a article 
Secondary data advantage
Inexpensive
The desired information may already exist
Therefore it Requires minimal effort making it inexpensive
Secondary data disadvantage
Quality may be poor
Information may be outdated or incomplete
Challenges the validity of the conclusions

Meta analysis
A Type type of secondary data that involves combining data from a large number of studies
Meta-analysis advantage
Increases validity of conclusions
The eventual sample size is much larger than individual samples
 increases the extent to which generalisations can be made
Meta-analysis disadvantage
Publication bias
researchers may not select all relevant studies leaving out negative or non-significant results
 incorrect conclusions are drawn
Advantage of using a mean
Sensitive
Includes all the scores in the dataset within the calculation
More of an overall impression on average rather than using median,mode
Disadvantages of using mean
May be unrepresentative
One very large or small number makes it distorted
The median and mode tend to not to be so easily distorted
Advantages of using the median
Unaffected by extreme scores
The median is only focused on the middle value
Maybe more representative of the data set as a whole
Disadvantages of using the median
Less sensitive than the mean
Not all scores are included in the calculation of the median
Extreme values may be important
Advantages of using the mode
Relevant to categorical data
When data is discreet i.e. represented in categories
Sometimes the mode is the only appropriate measure
Disadvantages of using the mode
An overly simple measure
There may be many modes in a data set
Not a useful way of describing data when there are many modes 
Advantage of the range
Easy to calculate
Arrange values in order to subtract the largest from the smallest
Simple Formula, easier than standard deviation
Disadvantage of the range
Does not account for the distribution of scores
Doesn’t indicate whether most numbers are closely grouped around the mean, or spread out evenly
Standard deviation is a much better measure of dispersion in this regard.
Advantage of using standard deviation
More precise than the range
Includes all values within the calculation
Displays a more accurate picture of the overall distribution in the data set
