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8. For which one of these relationships could we use a regression analysis?
a. Relationship between political party membership and opinion about Euthanasia
b. Relationship between gender and whether person has a mole
c. Relationship between weight and height
d. Relationship between eye colour (blue, brown, etc.) and hair colour (black, blond, etc.)
9. The correlation between two variables is given as r = 0.0. What does this mean?
a. The best straight line through the data is horizontal
b. There is a perfect positive relationship between the two variables
c. There is a perfect negative relationship between the two variables
d. All of the points must fall exactly on the horizontal line
10. Which of the following is true about residual error?
a. lower value is better b. higher value is better
c. Either a or b d. All of these
B. Fill in the blanks.
1. The regression line is also called least regression line.
2. is a perfect negative correlation.
3. are data points on the scatterplot that do not follow the pattern of the dataset.
4. Correlation is used to express an between two quantitative variables.
5. Crosstabs are used for values.
C. State whether the following statement is True or False.
1. Linear regression is a supervised learning algorithm.
2. It is not possible to design a neural network using linear regression.
3. In linear regression, we try to minimize the least square errors of the model to identify
the line of best fit.
4. Linear regression gives output as discrete values.
5. If the Pearson’s correlation coefficient, r, has a value 0.95, it indicates a weak relationship
between the two variables.
D. Match the following.
1. Linear Regression a. test the linear relationship between independent and dependent
continuous variables
2. Scatterplot b. represents y-intercept
3. Correlation coefficient c. best linear relationship between the independent and dependent
variables.
4. b in y = mx + b d. one observation
5. Dot on the scatterplot e. –1 to +1
288 Touchpad Artificial Intelligence (Ver. 2.0)-XI

