Reading...
Play button
Play button
Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
14 Cards in this Set
- Front
- Back
|
Scattergram
|
The scores of the independent (X) variable are arranged on the horizontal axis and the scores of the dependent (Y) variables along the vertical axis.
|
|
|
Regression Line
|
The line of best fit through the scattergram.
|
|
|
Purposes of a Scattergram
|
1)Information about the existence, strength and direction of the relationship
2)Checks the relationship for linearity 3)Can be used to predict the score of a case |
|
|
Existence of a Relationship on a Scattergram
|
The regression line lies at an angle
|
|
|
Strength of Relationship on a Scattergram
|
The tighter the spread around the regression line, the stronger the relationship.
|
|
|
Direction of Relationship on a Scattergram
|
Positive slop shows positive relationship, negative slope-negative relationship and no slope indicates "zero relationship"
|
|
|
Conditional Means of Y
|
The averages of Y for each X
|
|
|
Pearson's r
|
Measure of Association for interval-ratio data. Ranges from (-1 to 1)
|
|
|
Strength of Relationship for Interval Ratio Data
|
weak: 0.00-0.30
moderate: 0.30-0.60 strong: greater than 0.60 (Same as ordinal) |
|
|
Coefficient of Determination (r²)
|
A PRE measure which can be multiplied by 100 gives us the percentage that X helps us predict Y (explained variation).
When this percent in subtracted from 100 it gives us the unexplained variation. |
|
|
Explained Variation
|
Stronger linear relationships between X and Y will mean a greater value of the explained variation.
|
|
|
Making Assumptions for testing r for statistical significance.
|
1)Random sampling
2)Interval-ratio 3)Bivariate normal distribution 4)Linear Relationship 5)Homoscedasticity 6)Sampling distribution is normal |
|
|
Null Hypothesis for testing r for statistical significance.
|
H0: ρ=0.0
(H1: ρ≠0.0) |
|
|
Sampling distribution for testing r for statistical significance.
|
t distribution
degrees of freedom = (N-2) |
