correlations and data handling and analysis Flashcards
What is correlation
and what is a correlational design
A relationship between 2 variables
A correlational design is a way to test the relationship between 2 variables or how 2 or more things are related and if so how strongly
When do we use a correlational design
To test a hypothesis about a relationship
When looking for a relationship that would be unethical to manipulate for an experiment for example: stress causes poor health
what is an example of a correlational hypothesis
There will be a positive relationship between handspan in centimetres and height in centimetres
What is the correlation coefficent
+1 is a perfect positive correlation
-1 is a perfect negative correlation
0 is no correlation
What is the correlation and causation relationship
correlation does not mean causation
no iv or dv
what are the advantages and disadvantages of correlation analysis
Advantages
- Allows predictions to be made
- No manipulation
- Allows quantification/strength of the relationship
- Some hypothesis cannot be tested experimentally
negative
- extraneous relationships
- it cannot be assumed that one variable caused the other
- They may be intervening variables
what is quantitive and qualitative
Quantative = Data that focuses on numbers and frequency’s that can be counted
Qualitative = Data that doesn’t giver a number and cant be counted
what type of data do…. give?
experiments
observations
self-report techniques
correlation
experiments = quantitive because the DV is measured to establish cause and effect
observations = quantitive ( use a coding system)
self-report techniques =
- structured interview = quantitive
- unstructured interview = qualitative
correlations = correlation coefficient - quantitive
What are the positives and negatives of quantitive and qualitative data
quantative =
strengths - easy to analyse, easy to see patterns and make conclusions
weaknesses - oversimplifies, no explanations why
qualitative =
strengths - detailed since it includes thought + feelings
weaknesses - not easy to analyse
What is primary and secondary data
primary data = It has been taken by the researcher and been obtained first hand
secondary data = The data has already been collected by somebody else e.g. government data , NHS
What are the strengths and weaknesses of primary and secondary
primary
strengths - Directly relevant to the researchers aims
weaknesses - May not be accurate, Time and effort when planning and doing
secondary
strengths = inexpensive, little effort required
weaknesses = may be out of date or unreliable
What does a table show
What does a bar chart look like/show
What does a histogram show and look like
Table shows raw data in columns and rows
bar chart shows categorical data
and you leave spaces between the the bars
A histogram shows continuous data
there are no spaces between the bars
What does a line graph show /look like
what does a scatter graph show
line graphs show continuous data lines are connected by dots
A scatter graph shows the relationship between 2 co variables
What happens if you have a large and small standard deviation
large SD = large difference between scores ( not all effected by IV in the same way) over 5 is high
low SD = small difference between scores data is tightly packed (Under 5 is low)
What would you see with a normal distribution curve?
what does it measure
The mean, median and mode is the same
It measures the measure of central tendency
