Understanding Correlation through Scatter Graphs

What does correlation in data sets indicate?

• A direct cause and effect relationship

• None of the above

• The difference between two sets of data

• How closely two sets of data are related

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Why does correlation not imply causation?

• Because other factors might be influencing the results

• Because the data is always incorrect

• Because correlation only occurs in controlled environments

• Because the variables cannot be related

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What is an example of a positive correlation?

• No relationship between two variables

• As temperature increases, cola sales increase

• As temperature increases, cola sales decrease

• As the number of cats increases, the number of mice decreases

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What type of correlation is shown when both variables increase?

• Positive

• Negative

• No correlation

• Weak

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Which scenario describes a strong correlation?

• Data points are scattered widely from the line of best fit

• Data points form a circular pattern

• Data points do not follow any specific pattern

• Data points closely follow the line of best fit

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What does a negative correlation indicate?

• Both variables decrease together

• As one variable increases, the other decreases

• Both variables increase together

• No change in variables

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Which example shows a strong negative correlation?

• Increase in temperature and decrease in cola sales

• Increase in temperature and increase in cola sales

• Increase in cats and decrease in mice

• No change in variables with changes in another

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What can be inferred if there is no correlation between two variables?

• Both variables will always increase

• The variables are completely dependent on each other

• The variables are unrelated

• One variable causes changes in the other

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