1. Understanding Research Results: Description and Correlation

2. Analyzing the results of research investigations
Three basic ways to describe results
Comparing group percentages
Correlating individual scores
Comparing group means

3. Frequency distributions
Indicates the # of individuals that receive each possible score on a variable
Graphing frequency distributions
Pie charts
Bar graphs
Used for nominal data
Frequency polygons
a.k.a. line graph
A line is drawn to represent the relationship between variables

4. Descriptive statistics
Allow researchers to make precise statements about the data
Two types of stats are needed to describe data
Central tendency – tell us what the sample is as a whole
Mean-
Median-
Mode-
Variability

5. Descriptive statistics
Allow researchers to make precise statements about the data
Two types of stats are needed to describe data
Central tendency
Variability – the amount of spread in a distribution of scores
Standard deviation -calculated by taking the square root of the arithmetic average of the squares of the deviations from the mean in a frequency distribution
Variance -the average squared deviation of each number from its mean

6. Correlation coefficients: describing the strength of relationships
Correlation coefficient – a statistic that describes how strongly variables are related to one another
Pearson r
Type of correlation coefficient
Designed to detect only linear relationships
Used when both variables have interval or ratio scale properties
Provides info about the strength of the relationship and the direction of the relationship
0 = no relationship, 1 = strong positive relationship, -1 = strong negative relationship
The closer to 1, the stronger the relationship

7. Correlation coefficients: describing the strength of relationships
Pearson r
Data can be visualized in a scatterplot
A scatterplot shows
An indicator of effect size; it indicates the strength of the linear association between two variables
Calculated using pairs of observations from each subject
Curvilinear relationship
A scatterplot can still be constructed

8. Effect size
A general term that refers to the strength of association between variables
Correlation coefficients are calculated to indicate the magnitude of the effect of the IV on the DV
Values range from ______________
Provides a scale of values that is consistent across all types of studies

9. Regression equations
Calculations used to predict a person’s score on one variable when that person’s score on another variable is already known
For example, the use of SAT scores to predict college performance
General form is Y = a + bX
Y = score we wish to predict
X = known score
a = a constant

10. Multiple correlation
The correlation b/w a combined set of predictor variables and a single criterion variables
Used to combine a # of predictor variables to increase the accuracy of prediction of a given criterion or outcome variable
The resulting R value provides an indication of the goodness of fit of the model
Symbolized as R
Y = a + b1*X1 + b2*X bn*Xn
Y: criterion variable (predicted GPA)
X: predictor variables
a: constant
b: scores on the predictor variables (grades, GRE score)