Upgrade to remove ads
Busy. Please wait.
Log in with Clever
or

show password
Forgot Password?

Don't have an account?  Sign up 
Sign up using Clever
or

Username is available taken
show password


Make sure to remember your password. If you forget it there is no way for StudyStack to send you a reset link. You would need to create a new account.
Your email address is only used to allow you to reset your password. See our Privacy Policy and Terms of Service.


Already a StudyStack user? Log In

Reset Password
Enter the associated with your account, and we'll email you a link to reset your password.

Dissertation Data

        Help!  

Question
Answer
b-values   Unknown quantities in multiple regression. Tell us about the relationship between the outcome and each predictor. What degree each predictor affects the outcome if the effects of all other predictors are constant.  
🗑
t statistic   Measure of whether the predictor is making a significant contribution to the model. If the t test associated with a b value is significant (less than .05) then the predictor is making a significant contribution.  
🗑
Beta - B   Tells the number of standard deviations that the outcome will change as a result of one standard deviation change in the predictor. Provides a better insight into the importance of a predictor in the model.  
🗑
VIF   Assumption of no multicollinarity. Value less than 10 - no cause for concern. Average of VIF is substantially greater than 1 - regression may be biased.  
🗑
R2 in Multiple Regression   Measure of how much of the variability in the outcome is accounted for by the predictors. Useful measure of the substantive importance of an effect.  
🗑
Skewness   Lack of symmetry.  
🗑
Kurtosis   Pointyness.  
🗑
Positively Skewed   Frequent scores are clustered at the lower end and the tail points toward higher or positive positions.  
🗑
Negatively Skewed   Frequent scores are clustered at the higher end and the tail points toward lower more negative scores.  
🗑
Positive Values of Skewness   Pile up of scores on the left.  
🗑
Negative Values of Skewness   Pile up of scores on the right.  
🗑
Platykurtic Distribution   Many scores in the tails "Heavy Tailed" and is quite flat. Flat like a PLATEAU.  
🗑
Leptokurtic Distribution   Thin in tails and look pointy. LEAPT up in the air.  
🗑
r - Pearson Correlation   Value lies between -1 and 1. Standardized measure commonly used to measure the size of an effect.  
🗑
r - +/- .1   Small Effect  
🗑
r - +/- .3   Medium Effect  
🗑
r - +/- .5   Large Effect  
🗑
r = +1   2 variables are perfectly positively correlated.  
🗑
r = -1   2 variables are perfectly negatively correlated.  
🗑
Multiple Regression   Seeks to predict an outcome from several predictors.  
🗑
Adjusted R2   Measure of how well a model generalizes. Like the values to be close to R2.  
🗑
Durbin-Watson   Measures whether the assumption of independent errors is tenable. The closer to 2 the better. Less than 1 or greater than 3 = ALARM.  
🗑
ANOVA Table for Regression   Tests whether the model is significantly better at predicting the outcome than using the means as a "best guess." Look for values less than .05.  
🗑
VIF   Variance Inflation Factor - indicates whether a predictor has a strong linear relationship with the the other predictors. Value of 10 is worrisome (Myers, 1990) and if average is greater than 1, multicollinearity may be biasing the model.  
🗑
Multcollinearity   Exists when there is a strong correlation between 2 or more predictors in a regression model. This increases the probability that a good predictor of the outcome will be found non-significant and rejected from the model (a type II error).  
🗑
Type I Error   Saying something is when it is not.  
🗑
Type II Error   Saying something is not when it is.  
🗑


   

Review the information in the table. When you are ready to quiz yourself you can hide individual columns or the entire table. Then you can click on the empty cells to reveal the answer. Try to recall what will be displayed before clicking the empty cell.
 
To hide a column, click on the column name.
 
To hide the entire table, click on the "Hide All" button.
 
You may also shuffle the rows of the table by clicking on the "Shuffle" button.
 
Or sort by any of the columns using the down arrow next to any column heading.
If you know all the data on any row, you can temporarily remove it by tapping the trash can to the right of the row.

 
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.

  Normal Size     Small Size show me how
Created by: rrsiers
Popular Standardized Tests sets