2:Descriptive Stats Reslationships Between Varibles Part 2 Flashcards
Pearson r
Two quantitative variables
Correlation coefficient
-linear relationship between 2 QUAN variables (interval or ratio) normal
Sign of r tells u direction of relations between variables
Magnitude of r absolute value tells u the strength of linear relationship between variables
Cohens d
One dichotomous categorical and one quantitative to compare means of two distributions
Scatterplot
X= IV
Y= DV
Display paired data from a set of individual cases
-may include best fit
Positive correlation
Increase in one is increase in other. Positive slope
Negative correlation
Increase in one variable accompanies a decrease in other. Negative slope.
Magnitude of r
The larger the magnitude of r, the closer the data points are to the best-fit straight line.
Coefficient determination: r^2 percentage of variation in B explained by A
Side by side box plots
Comparing means. Data from multiple
Groups or conditions compared side by side.
Bar graphs
Comparing means.
Display means as bars extending from categorical axis
-heigh/length of each represents mean value of quantity variable for cases at that value of categorical variable
-error bars illustrate variability as whiskers extending from top of bar
EMPHASIZE DIFFERENCES BETWEEN MEANS
Factorial designs
One categorical variable along the categorical axis (X)
-other categorical variable in legend
Line graphs
Comparing means
Means as points connected by line segments
-x is ordinal scale or higher
-if x variable is quantitative but discrete, the x axis is scaled with units (distance is meaningful)
-EMPHASIZE CHANGES IN MEAN VALUE OF Y AS FUNCTION OF X
Functional relationships
Characterized based on how the value of Y changes as the X increases
Monotonic: continuously increasing or decreasing
Nonmonotonic: contains at least one reversal in direction
Asymptotic: if curve levels off
Cohens d effect size
Difference in means relative to pooled standard deviation of 2 distributions
-less overlap of distributions = larger cohens d = larger effect size
(Stronger relationship or association)
M1-M2/ SD
If both variables categorical
Must display counts or proportions for number of cases at each combo
- frequency table
- multicolor or patterned histogram with two or more series
- side by side pie graphs