Standardizing Data and the Normal Distribution Part 2
About the Lecture
The lecture Standardizing Data and the Normal Distribution Part 2 by David Spade, PhD is from the course Statistics Part 1. It contains the following chapters:
- Scatterplots and Correlation
- Making a Scatterplot
- Choosing X and Y
- What is Correlation?
- Finishing the Calculation
- Correlation and Causation
Included Quiz Questions
What information can we gain from a scatterplot?
- We can determine the form of a relationship between two quantitative variables.
- We can determine the form of a relationship between two categorical variables.
- We can determine the correlation between two quantitative variables.
- We can determine the strength of a relationship between two categorical variables.
- We can determine the slippage between two quantitative variables.
If two quantitative variables are deemed to have a positive relationship, what does that mean?
- This means that as the values of the X variable increase, the values of the Y variable increase.
- This means that as the value of the X variable increases, the value of the Y variable decreases.
- This means that as the value of the X variable decreases, the value of the Y variable increases.
- This means that the values of X and Y are all positive.
- The values of X and Y are all positive or zero.
Which of the following is NOT true about correlation?
- Correlation measures the strength of a linear relationship between two categorical variables.
- Correlation measures the strength of a linear relationship between two quantitative variables.
- A correlation coefficient takes values between -1 and 1.
- Correlation indicates the direction of a linear relationship between two quantitative variables.
- A correlation coefficient may take on the value of 0.
Which of the following is a TRUE statement?
- Correlation does not have a unit of measurement.
- Two quantitative variables with correlation 0.6 have a stronger linear relationship than two quantitative variables with correlation -0.6.
- If two quantitative variables are highly correlated, it can be concluded that changing the value of the explanatory variable causes the change in the response variable.
- Outliers have little effect on the correlation.
- Two quantitative variables with correlation 0.6 have a stronger linear relationship than two quantitative variables with correlation -0.8.
Under which of the following situations is correlation an appropriate measure of the strength of the relationship between two variables?
- Correlation is appropriate when measuring the strength of a relationship between two quantitative variables that appear to be linearly related and have no outliers present.
- Correlation is appropriate when measuring the strength of the relationship between two categorical variables.
- Correlation is appropriate when measuring the strength of a relationship between two quantitative variables that appear to be linearly related and have several outliers present.
- Correlation is appropriate for measuring the strength of the relationship between two quantitative variables when the relationship appears nonlinear.
- Correlation is appropriate when measuring the strength of a relationship between two quantitative variables that appear to have a logarithmic relationship.
Which of the following numbers is likely to represent the correlation coefficient of two variables having a strong positive association?
- 0.89
- -1.3
- -0.89
- 0
- 1.5
Which of the following numbers is likely to represent the correlation coefficient of two variables having no association?
- 0
- -1.3
- -0.89
- 0.89
- 1.5
Which of the following numbers is likely to represent the correlation coefficient of two variables whose scatterplot is downward sloping?
- -0.89
- -1.3
- 0
- 0.89
- 1.5
Which of the following numbers is likely to represent the correlation coefficient of two variables whose scatterplot is upward sloping?
- 0.45
- -1.1
- -0.45
- 0
- 1.7
What is one characteristic to evaluate in a scatterplot?
- Direction
- Liquidity
- Height
- Width
- Z-axis
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Author of lecture Standardizing Data and the Normal Distribution Part 2
David Spade, PhD
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I learned a lot with this lecture. Really, I like the way of explanation. I will recommend this lecture to everybody who is really wanted to study statistics.
