Term
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Definition
| effects of a treatment using a repeated measures design, that persist so long that they are present even while the participants are receiving additional treatments |
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Term
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Definition
| create problems for a within subjects design as you many believe the participants behaviour is due to the treatment just administered, when in reality the behaviour is due to the lingering effects of a treatment administered earlier. |
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Term
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Definition
| after several treatments, subjects of a within subjects design may become sensitive to what the hypothesis is. And two, the participant may behave differently because of this. |
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Term
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Definition
| If participants who receive one sequence of treatments score differently than those participants who receive the treatment in a different sequence, there is a sequence effect. Does getting the treatment in one particular sequence cause a group to score differently than a group receiving the treatments in a different sequence? |
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Term
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Definition
| After performing a task several times, a participants performance may improve. In a within subjects design, this may be a confounding variable. |
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Definition
| Decreased performance of the dependent variable due to being tired or less enthusiastic. Problem of Within subjects design |
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Term
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Definition
| The order that the participant receives the treatment, effects behaviour. Major problem of within-subjects design. |
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Term
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Definition
| A procedure used with 1-way anovas when Levene's test of homogeneity is found to be significant, when using unequal sample sizes. |
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Term
| Violation of Homogeneity of Variance Assumption with 2-way Anova (unequal sample sizes) |
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Definition
1. Switch to non-parametric techniques
2. Follow a special procedure
3. Calculate unweighted means, and then calculate F ratio based on the unweighted means |
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Term
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Definition
| Multiple weighted cell means by N for each group (ie N = 14 & N = 12) and add the two scores together. Then divide by by the total sample size ie (14+12) |
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Term
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Definition
| Used when there is a violation of the homogeneity assumption, using unequal sample sizes. The means are unweighted because the are not divided by their sample size. Instead each mean is added together and dived by two |
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Term
| Levene's Test of Equality of Error Variance |
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Definition
| Some common statistical procedures assume that variances of the populations from which different samples are drawn are equal. Levene's test assesses this assumption. |
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Term
| Analyzing Unbalanced Designs |
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Definition
| In general, using Type III Sum of Squares (unweighted means) is the best and most common approach to analysis of unbalanced designs |
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Term
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Definition
1. The population variances of the repeated measurements are equal
2. The population correlations among all pairs of measures are equal
3. Violation of the assumption of sphericity is serious: results in increased type 1 errors |
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Term
| Normality Assumption (Repeated Measures Design) |
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Definition
| Repeated measures designs assume that the scores in all conditions are normally distributed |
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Term
| Independence Assumption (Repeated Measures Design) |
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Definition
| It is not assumed that the scores of a given subject are independent of each other, since the point of analysis is that they are dependent. |
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Term
| When do we use an Analysis of Covariance? (ANCOVA) |
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Definition
1. To test the differences between group means when we know that an extraneous variable affects the outcome variable.
2. Used to Control known extraneous and confounding variables. |
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Term
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Definition
1. Reduces Error Variance: by explaining some of the unexplained variance (SSerror), the error variance in the model can be reduced.
2. Greater Experimental Control: by controlling known confounds, we gain greater insight into the effect of the predictor variable(s) |
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Term
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Definition
| Covariance is a measure of how much two variables change together and how strong the relationship is between them.[1] Analysis of covariance (ANCOVA) is a general linear model which blends ANOVA and regression. ANCOVA evaluates whether population means of a dependent variable (DV) are equal across levels of a categorical independent variable (IV), while statistically controlling for the effects of other continuous variables that are not of primary interest, known as covariates (CV). Therefore, when performing ANCOVA, the DV means are adjusted to what they would be if all groups were equal on the CV. |
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Term
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Definition
| the mean of the dependent variable for each group |
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Term
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Definition
| the mean of the dependent variable for each group |
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Term
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Definition
| the mean of the covariate for each group |
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Term
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Definition
| the mean of the covariate for all groups |
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Term
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Definition
| Standardized way to report the difference between 2 means |
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Term
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Definition
| (sample mean of the experiment minus the sample mean of the control group) over the standard deviation of the control group |
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Term
| Parts of a research article |
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Definition
| Introduction, methods, results, and discussion |
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Term
| Introduction of a research article |
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Definition
| literature review that builds a theoretical case for the research |
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Term
| Methods section of a research article |
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Definition
| Descriptions of the participants, measures, and procedures |
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Term
| Results section of a research article |
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Definition
| statistical tests completed, pattern of findings displayed |
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Term
| Discussion section of a research article |
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Definition
| Interpretation of results. Does it support the theory? Written in APA style. |
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Term
| According to the Activation-Decision-Construction model, what skill must an effective liar posses? |
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Definition
| Lying requires verbal skill |
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Term
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Definition
| An experimental design in which each subject (DV) is randomly assigned to only one of the treatment conditions (IV) |
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Term
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Definition
| all participants are exposed to all levels of the IV |
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Term
| Should measures of verbal ability correlate more with lying or truth-telling? |
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Definition
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Term
| According to the compensatory-encoding theory, how can readers compensate for weak reading skills? |
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Definition
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Term
| Compensation use in Compensatory-Encoding Theory |
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Definition
| Pauses, lookbacks, rereads, soundouts |
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Term
| Reading skill measures used in the Compensatory-Encoding Theory |
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Definition
| Decoding accuracy, Semantic latency, semantic accuracy, and working memory capacity |
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Term
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Definition
| a correlation between [a variable that can only take 2 values] and [a continuous variable] |
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Term
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Definition
| When the effects of one factor change for different levels of another factor, we say there is an interaction. |
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Term
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Definition
| Using one variable to predict another. We can understand the relationship between two quantitative variables to make predictions. |
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Term
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Definition
| Is just an equation of a straight line through the data. |
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Term
| Predicted Value (Regression) |
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Definition
| In linear regression, it is the estimate made from the model.Notation is: y(hat) |
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Term
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Definition
| The difference between the observed value and the associated predicted value. Always subtract the predicted value from the observed value. |
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Term
| Negative Residual (Regression) |
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Definition
| Means the predicted value is too big. An overestimation. |
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Term
| Positive Residual (Regression) |
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Definition
| The model has made an underestimation. |
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Term
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Definition
| Tells how rapidly the predicted value of y changes with respect to x. |
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Term
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Definition
| Tells us where the line his the y-axix |
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Term
| Coefficients (Regression) |
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Definition
| The b's are called the coefficients of the linear model. |
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Term
| Line of Best Fit (Regression) |
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Definition
| the line for which the sum of squared residuals is smallest, the "least squared line." |
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Term
| Slopes vs Correlations (Regression) |
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Definition
| Correlations don't have units, but slopes do. How x and y are measured, what units they have, doesn't affect their correlation, but can change their slope. |
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Term
| Units of the Slope (Regression) |
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Definition
| The units of the slope are always the units of y per unit of x. |
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Term
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Definition
| Commonly called regression lines |
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Term
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Definition
Conditional Probability. The probability of A given B.
P(A|B) = P(A and B)/P(A) |
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Term
| P(A and B) = P(A) x P(A|B) |
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Definition
| The General Multiplication Rule: for compound events does not require the events to be independent. |
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Term
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Definition
| The probability of one event does not change the probability, when the other event occurs. |
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Term
| Disjoint or Mutually Exclusive Events |
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Definition
Mutually exclusive events cannot be independent. They have no outcomes in common, so if one occurs, the other doesn't (i.e you cannot get both and A and a B in Statistics).
A common error is to treat disjoint events as if they were independent, and apply the Multiplication Rule for independent events. |
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Term
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Definition
| Go into the margins of a contingency table |
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Term
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Definition
| Go into the center of a contingency table |
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