This Figure shows a scatter plot of the relationship between scores on a reading test and scores on a writing test. Based on what you can see from the plot there is:
A negative relationship between writing and reading scores.
A positive relationship between writing and reading scores.
No relationship between writing and reading scores.
A weak relationship between writing and reading scores.
Pregunta 2
Pregunta
A researcher explores the relationship between a measure of vanity and the number of selfies posted on-line in a month. The data showed that r = .50. We can therefore determine that Vanity accounted for what percentage of variance in number of selfies posted on-line in a month?
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25%
50%
0.5%
5%
Pregunta 3
Pregunta
The process to rule out the influence of one or more additional variables on the relationship between the X and the Y variable is:
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regression
Yate's correction
partial correlation
bi-variate correlation
Pregunta 4
Pregunta
When interpreting a correlation analysis, it is important to look at which of the following features?
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The strength of relationship
The direction of relationship
The statistical significance of relationship
All of the above
Pregunta 5
Pregunta
Which of the following does a scatterplot show?
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The mean value associated with two variables.
The proportion of data falling into one of two categories.
The frequency with which values appear in the data.
Scores on one variable plotted against scores on a second variable.
Pregunta 6
Pregunta
What does the calculation of Covariance tell us?
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Whether the scores we have on variables X and Y are normally distributed.
The extent to which variability on one variable is associated with a predictable change in another variable before standardisation.
The extent to which variability on one variable is associated with a predictable change in another variable after standardisation.
The percentage of explained variance between the two variables of interest.
Pregunta 7
Pregunta
The table below shows us the zero order correlations and the partial correlations between a measure of quality of life after undergoing cosmetic surgery and participants self-reported level of depression , whilst controlling for a measure of quality of life BEFORE undergoing cosmetic surgery. Which of the following is correct.
The proportion of variance explained is reduced once we control for the variability of our measure of quality of life BEFORE undergoing cosmetic surgery.
The proportion of variance explained increases once we control for the variability of our measure of quality of life BEFORE undergoing cosmetic surgery.
Controlling for the variability of our measure of quality of life BEFORE undergoing cosmetic surgery has no effect on the proportion of variance explained.
None of the other options are correct
Pregunta 8
Pregunta
Which of the following is the best description of the difference between a positive and a negative correlation?
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A positive correlation shows that changes on X and Y variables are going in the same direction, whilst a negative correlation is showing us that changes on our X and Y variables are going in different directions.
A positive correlation shows that changes on X and Y variables are going in the same direction, whilst a negative correlation is showing us that there is no variability on our X and Y variables.
We get negative correlations when we control for the influence of a third variable, and the third variable shares a lot of the variance.
A negative correlation is a weak one, whilst a positive correlation is a strong one.
Pregunta 9
Pregunta
Which of the following statements is NOT true:
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The coefficient of determination is calculated by taking our equation for covariance and dividing by the Mean Score of the two variables of interest
The coefficient of determination gives us a value relating to covariance that is in standardised units.
The coefficient of determination is calculated by taking our equation for covariance and dividing by the Standard Deviation of the two variables of interest
The correlation coefficient gives us a measure of the degree to which the two variables of interest vary together, in unstandardized units of measurement.