statistics Flashcards
What is meant by the term quantitative data? [2 Marks] + strength
- expressed numerically (1).
- can be gained from individual scores in experiments eg, scores on test
- more simple to analyse, allows comparison between groups
- easier to make conclusions about behaviour
-whereas qual is wordy more difficult to summarise statistically
What is meant by the term qualitative data? [2 Marks] + strength
- expressed in words/ is descriptive data (1) -such as a diary entry or answers from open questions in a questionnaire (1).
- provides rich detail and depth allows ppts to develop thoughts and feelings on subject
- greater understanding of behaviour being studied (contextualise)
- whereas quan lacks depth
Describe nominal data
- data in form of categories
- eg; hair colour, favourite team
describe ordinal level data
- data ordered/ranked in some way
- does not have fixed intervals
- subjective opinions are an example of ordinal level data
eg; items recalled in memory test, ratings
Describe interval level data
- data is standardised/ universal
- data is factual measures, eg; time (seconds)
- based on numerical scales
what is meant by the term primary data
(2 marks)
- gathered directly from the ppts and is specific to the aim of the study, data collected by questionnaires
str - collected 1st hand for the aim, increases overall internal val
wkn - involves time and effort to get data
what is meant by the term secondary data
(2 marks)
- collected by a third party, not specifically for the aim of the study and then used by the researcher
str - easily accessed and requires minimal effort
wkn - poor quality or have inaccuracies
what is meant by the term meta analysis
(2 marks)
- uses secondary data gains data from a large number of studies which have investigated the same research questions and method of research
- combines info from all studies to make conclusions about behaviour
What does a high SD and low SD tell us
- High = more spread so more variation, less consistent, more individual differences
- Low = less spread, less variation in score, more consistent and less individual differences
Structure of drawing a graph question
- Correctly identifying which graph you should be drawing
- Plot the correct data
- Give the graph a title
- Label the axis appropriately (OPERATIONALISE THEM)
- Have an appropriate scale on the y axis
When are bar charts used
- Used to display NOMINAL/ORDINAL (DISCRETE) data.
- Used to compare conditions.
- THE BARS NEVER TOUCH.
When are histograms used
- Used to display INTERVAL (CONTINUOUS) data.
- Shows data within conditions
- THE BAR SHOULD ALWAYS BE TOUCHING
When are scatter graphs used
- Used to display a RELATIONSHIP between two co-variables
- You plot correlations on these
- Remember – each X represents a ppt.
When you are interpreting statistical tests there are six statements you have to work through to decide
whether your results are significant. These are:
- One or two tailed research hypothesis?
- Number of participants (N=) in a chi-square it is degrees of freedom (df)
- Level of significance (if it doesn’t state the p-value assume it is less than 5%)
- Identify the observed/calculated value (in the text)
- Identify the critical value (in the table)
- Interpret the findings using the statement under the critical value table
Define what is meant by a Type I Error [2 Marks]
- researcher has used a lenient P value.
- researcher thinks the results are significant when actually due to chance/error.
- So they wrongly accept alt hypothesis and wrongly reject the null.
- known as a false positive
