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b-weights in bivariate regression correct answers Unstandardised regression coefficients indicating the amount of change in Y' for each change of 1 in X b-weights in multiple regression correct answers Unstandardised regression coefficient indicating the amount of change in Y' for a change of 1 ...

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3003PSY Final || with A+ Guaranteed Solutions.
b-weights in bivariate regression correct answers Unstandardised regression coefficients
indicating the amount of change in Y' for each change of 1 in X

b-weights in multiple regression correct answers Unstandardised regression coefficient
indicating the amount of change in Y' for a change of 1 in a single predictor (X) when all other
Xs are held constant - PARTIAL SLOPE

SSregression correct answers systematic component of variance
distance of predicted scores from the mean

SSresidual correct answers error component of variance
distance between predictor score and actual scores

What is the equation for variance explained? correct answers SSreg/SStot

What are the stages of linear modelling? correct answers 1. Model specification
2. Parameter estimation
3. Model checking
4. Prediction

What are the assumptions of regression? correct answers Normality of residuals
Homoscedasticity
Linearity
Independence of errors

What is homoscedasticity? correct answers constant variance of residuals across predictors

What does normality of residuals mean? correct answers That the residuals are centred around 0

Explain the assumption of independence of residuals. correct answers Residuals must be
uncorrelated with Y

What does the assumption of linearity mean? correct answers That there is a linear relationship
between each predictor and the criterion

What is the difference between parametric and non-parametric tests? correct answers parametric
tests involve the estimation of at least one population parameter, they have assumptions about
the specific shape of the distribution and assume DV measured at an interval or ratio level
non-parametric tests do not include either of these

What are the advantages of non-parametric tests? correct answers no assumptions of normality or
homoscedasticity
ideal for small samples

, use of ranks reduces effects of outliers

What is the difference between Pearson's r and Spearman's rho? correct answers Spearman's rho
is still calculated using Pearson's r formula but the data is instead ranked

When would you use Spearman's rho? correct answers If the assumptions of Pearson's r are not
met
i.e. if the data is not interval or ratio, normally distributed, and linear
OR if the data naturally falls in ranks, has extreme outliers or there is a monotonic relationship

What is a monotonic relationship? correct answers As x increases, Y increases but not
necessarily at a constant rate

Advantages of Spearman's rho correct answers can be used when variables are severely skewed
converts a monotonic relationship into a straight line fit
can be used for small samples

What is point-biserial correlation? correct answers Used for describing the relationship in
dichotomous variables

How do you interpret point-biserial correlation (rpb)? correct answers The sign determines the
direction of the relationship
interpreted the same as Pearson's r

What is the relationship between t and rpb correct answers independent t test would give the
same answer as rpb

What is an N=1 design? correct answers the intensive study of responding within an individual
across time
i.e. design involving only 1 participant

What characteristics of data can be used to decide whether changes are reliable (N=1 designs)?
correct answers changes in mean
changes in trend line
shift in level
latency of change
THESE ARE DETERMINED BY EXAMINING THE GRAPH VISUALLY

How do N = 1 designs exert control? correct answers remove between subjects threats to validity
baseline if stable indicates absence of extraneous factors

AB designs correct answers 1 control phase and 1 intervention phase
susceptible to maturation, sequencing and practice effects

ABA designs correct answers baseline -> treatment phase -> baseline
if treatment has an effect, we should see a return to baseline (reversal)

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