Question

question 1
matching words
correlation
linear model
residual
predicted variable
coefficient of determination
linearity
slope coefficient
intercept
scatter plot
total variation

1. the difference between the predicted value and the observed value
2. it represent the estimated change in the dependent variable for every one unit change in the independent variable.
3. the relationship between the independent and dependent variables must be a straight line.
4. the predicted value of the dependent variable when the independent variable is equal to zero
5. the difference between an observed dependent variable and the mean of the observed dependent variable.
6. a graph that displays the relationship between two variables
7. an estimate of the mean value of the dependent variable for any given value of the independent variable
8. measures the strength of the linear association between two quantitative variables.
9. an equation of a straight line through the data.

10.its value indicates the proportion of the variance in the dependent variable that the independent variable can explain.

Explanation:

1. Residual is defined as the difference between the predicted value and the observed value in a regression - related context.
2. The slope coefficient represents the estimated change in the dependent variable for every one - unit change in the independent variable.
3. Linearity implies that the relationship between the independent and dependent variables must be a straight line.
4. The intercept is the predicted value of the dependent variable when the independent variable is equal to zero.
5. Total variation is the difference between an observed dependent variable and the mean of the observed dependent variable.
6. A scatter plot is a graph that displays the relationship between two variables.
7. The predicted variable is an estimate of the mean value of the dependent variable for any given value of the independent variable.
8. Correlation measures the strength of the linear association between two quantitative variables.
9. A linear model is an equation of a straight line through the data.
10. The coefficient of determination indicates the proportion of the variance in the dependent variable that the independent variable can explain.

Answer:

1. Residual
2. Slope Coefficient
3. Linearity
4. Intercept
5. Total variation
6. Scatter Plot
7. Predicted Variable
8. Correlation
9. Linear Model
10. Coefficient of Determination