Correlation Analysis Flashcards

1
Q

What is the goal of correlational analysis in scientific research?

A

To determine if there is a relationship between two or more variables.

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2
Q

How does correlational analysis differ from other statistical analyses?

A

Variables are observed in their natural state rather than being manipulated.

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3
Q

What does a correlational analysis measure?

A

How two quantitative variables are related.

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4
Q

What do researchers look for when plotting data in a correlational analysis?

A

If there is a linear or curvilinear relationship.

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5
Q

What is the importance of calculating the strength of the relationship in correlational analysis?

A

To determine if there is a statistically significant relationship.

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6
Q

True or False: Correlation implies causation.

A

False

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7
Q

What defines a positive correlation?

A

Both variables increase together.

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8
Q

What defines a negative correlation?

A

As one variable increases, the other decreases.

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9
Q

What happens on a scatterplot when there is no correlation?

A

Points are spread out and do not resemble a specific line.

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10
Q

What is the correlation coefficient represented by Pearson’s r?

A

A statistic that indicates the degree and direction of the relationship between two variables.

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11
Q

What is the range of values for Pearson’s r?

A
  • -1: Perfectly negative correlation
  • 0: No correlation
  • +1: Perfectly positive correlation
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12
Q

What does an r-value of -0.62 indicate?

A

Moderate, negative correlation.

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13
Q

What is the impact of outliers on correlation coefficients?

A

They can strongly impact the correlation coefficient in one direction or another.

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14
Q

What type of data does Spearman’s ρ (rho) analyze?

A

Ordinal data or non-normal continuous data.

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15
Q

True or False: Pearson’s r is used for nonparametric tests.

A

False

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16
Q

What does a strong positive correlation indicate?

A

As the values of X increase, so do the values of Y.

17
Q

What is the definition of covariance?

A

The direction of the linear relationship between two variables.

18
Q

Fill in the blank: A _______ relationship exists when the plotted ordered pairs approximate a straight line.

19
Q

What is a curvilinear relationship?

A

When the relationship between two variables does not follow a linear pattern.

20
Q

What does a correlation coefficient less than r = -0.5 or greater than r = +0.5 indicate?

A

A potential relationship between two variables.

21
Q

What is one limitation of correlational studies?

A

They cannot verify a cause-and-effect relationship.

22
Q

What is a common method to visually represent correlations?

A

Scatterplots.

23
Q

What is the role of the independent variable in a correlational analysis?

A

It explains changes in the dependent variable.

24
Q

What is the significance of the correlation coefficient in a dataset?

A

It indicates the degree of relationship or consistency between variables.

25
What should researchers consider when studying correlations?
The range of values and the presence of outliers.
26
What is the difference between parametric and nonparametric tests?
Parametric tests assume population parameters, while nonparametric tests do not.
27
What is an outlier?
An outlier is an extreme value that is either much smaller than or much larger than most of the values in a dataset.
28
How do outliers affect correlation coefficients?
Outliers can strongly impact the correlation coefficient in one direction or another.
29
What is the importance of considering outliers in research?
It is important to determine if outliers are errors or true values to understand the true relationship between variables.
30
True or False: Outliers always indicate an error in the data.
False
31
Fill in the blank: If an outlier is truly part of the range of data, it may provide a more _______ representation of the population.
[accurate]
32
What should researchers do before removing outliers from a dataset?
Researchers should ensure there is evidence that outliers are the result of errors rather than true values.
33
When analyzing data, what can outliers skew?
Outliers can skew the results and cause an inaccurate measure of a relationship.