Karteikarten
Statistis Lecture 6 - Relationships between variables
Karten in diesem Stapel (11)
- 1There are two types of variablesindependent/predictor: the variables you manipulate
depdendent: the variables you measure (also questionnaire items) - 2The Different Scales of measurement (this is review)
- 3What does it mean to assess relationships in PsychologyWe've only looked at the effect of one variable on another, when in reality in psychology, multiple variables are often asessed. e.g.
E.g., how many chocolate bars do I eat as the exam draws closer?
Variable 1 = # chocolate bars
Variable 2 = days until exam - 4Using tables in certain situations (Two nominal variables, e.g. gender and whether previously hospitalized)
- 5Using tables in certain situations (Two continuous variables, e.g. age groups or income bands)
- 6Best diagram for two continuous variablesA scatterplot with a line of best fit
- 7Summary for using Diagrams
- 8Line of Best fitLine of best fit is used to indicate the general trend of the individual data points in terms of one line
- 9Determining Covariance
- 10CorrelationsCovariance is used to calculate correlations
Covariance and correlations are different numbers
Correlations have two characteristics
Magnitude:
Between 0 and 1.
A value of ‘0’ means no relationship.
A value of ‘1’ means a perfect relationship.
Direction:
Negative Correlation vs. Positive Correlation.
For example, -.67 or .56. - 11Characteristics of a CorrelationA correlation coefficient:
quantifies how well the best fit line explains the data
gives direction of relationship.
A correlation has two features
Magnitude
direction
A correlation of zero shows no relationship.
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- University Undergraduate Statistics Karteikarten am Statistis Lecture 6 - Relationships between variables, erstellt von sarahderveeuw am 05/05/2015.
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