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PSY 395 Exam 4
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Gravity
Terms in this set (49)
Temporal precedence
does the casual variable come before the effect variable in time ?
covariance
does the casual variable related to the effect variable?
internal validity
are there no other alternate explanations for the results?
bivariate outliers
- combination of unusual scores on at least two variables
- particular problem in small sample sizes
linear relationship
any given change in an independent variable will always produce a corresponding change in the dependent variable
curvilinear relationship
relationship between two variables where as one variable increases, so does the other variable, but only up to a certain point, after which, as one variable continues to increase, the other decreases
restriction of range
- problem that arises when you don't have a full range of scores on one or both of your variable
- limited range
third-variable problem
outside factor that is effecting an outcome of correlation
moderator
a variable who different levels could change the relationship between the two variables
- are these two variables related for everyone?
mediator
- why are two variables related?
longitudinal designs
an observational research method in which data is gathered for the same subjects repeatedly over a period of time
cross-sectional correlation
analyzes data from a population, or a representative subset, at a single specific point in time
autocorrelation
Measures the same variable at different time points
cross-lag correlation
first measure of one variable is correlated with the second measures other variable.
intercept
that is, the point where the line crosses the vertical y-axis or horizontal x-axis
slope
measure of the steepness of a line, or a section of a line
unstandardized regression coefficient
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standardized regression coefficient
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ANOVA
analysis of variance, a statistical method in which the variation in a set of observations is divided into distinct components
F-Ratio or F-Statistic
the ratio of the between group variance to the within group variance
Factorial Design
design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors
Main Effect
the effect of an independent variable on a dependent variable averaging across the levels of any other independent variables
Interaction Effect
the effect of one of the variables differs depending on the level of the other variable
Within-Subjects Design
the same subjects perform at all levels of the independent variable
Between-Subjects Design
an experiment that has two or more groups of subjects each being tested by a different testing factor simultaneously
Mixed Design
analysis of variance model (also known as a split-plot ANOVA) is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures
How do outliers influence the relationship between two variables?
This can throw off statistical significance and cause other errors in the analysis data
How does sample size influence the impact that outliers can have on a correlation?
the smaller the sample size the more an outlier will effect the correlation that variables will have with one another.
How do you interpret the strength of a correlation?
how close the dots resemble a straight line as well as the slope that the dots line up with
What happens when you have a curvilinear relationship but conduct a linear regression/correlation?
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Why is restriction of range a problem in correlation designs? How can you solve it?
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What are primary components of a Cross-Lagged Correlation design?
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What factors of a cross-lagged correlation design can be used to establish temporal precedence?
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In the equation Y=a+bX, what are Y, a, b, and X?
a- the y-intercept
b- the slope of the line
X- the value established
Y- the end result of how a,b,&X effect each other
What is the interpretation of the intercept in linear regression?
Where the line crosses either the y or x - axis
What is the interpretation of the slope in linear regression?
the strength of a correlation
What is the difference between a predicted value and an observed value in linear regression?
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What is the difference between unstandardized (b) and standardized (Beta) regression coefficients?
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Under what circumstances can you compare regression coefficients in a single equation or model?
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What does it mean to "control for a variable" in multiple regression?
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How would you identify a moderator variable?
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How would you identify a problematic 3rd variable?
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How are ANOVA and t-tests related?
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What are three source of variance that are important in an ANOVA?
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How do you calculate the F-Ratio?
between group variance divided by within group variance
How do you interpret a F-Statistic (i.e. what factors are important)?
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You should also be able identify and interpret the various elements/statistics you would observe from SPSS output
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You should be able to identify and interpret main effects and interaction effects
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You should be able to describe the factorial design (ex. 2x3 or 2x2)
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