Bivariate Data

What does a positive association in bivariate data indicate?

• A positive association indicates that as one variable increases, the other variable also tends to increase.

• A positive association indicates that as one variable increases, the other variable tends to decrease.

• A positive association indicates that there is no relationship between the two variables.

• A positive association indicates that both variables remain constant regardless of each other.

What is the difference between correlation and causation?

• Correlation indicates a relationship between two variables, while causation implies that one variable directly affects the other.

• Correlation means that two variables are identical, while causation means they are unrelated.

• Correlation shows that two variables are dependent on each other, while causation shows that they are independent.

• Correlation is a statistical measure, while causation is a psychological concept.

What is the equation of a trend line?

• y = mx + b

• y = ax^2 + bx + c

• y = m + b

• y = mx - b

How can you use a trend line to make predictions?

• You can use a trend line to predict the value of the dependent variable by substituting the value of the independent variable into the trend line equation.

• You can use a trend line to determine the average of all data points without any calculations.

• You can use a trend line to visualize the data without making any predictions.

• You can use a trend line to find the maximum value of the independent variable.

What does the y-intercept represent in a trend line equation?

• The value of the dependent variable (y) when the independent variable (x) is zero.

• The slope of the trend line.

• The point where the trend line crosses the x-axis.

• The average value of the dependent variable (y) across all data points.

What does a negative association in bivariate data indicate?

• A negative association indicates that as one variable increases, the other variable tends to decrease.

• A negative association indicates that both variables increase together.

• A negative association indicates that both variables decrease together.

• A negative association indicates that there is no relationship between the variables.

How do you determine if a trend line is a good fit for the data?

• A trend line is a good fit if it closely follows the pattern of the data points and minimizes the distance from the points to the line.

• A trend line is a good fit if it intersects the y-axis at the origin.

• A trend line is a good fit if it has a steep slope regardless of the data points.

• A trend line is a good fit if it passes through all the data points.

How do you interpret the slope of a trend line?

• The slope of a trend line indicates the rate of change of the dependent variable (y) for each unit change in the independent variable (x).

• The slope of a trend line represents the total value of the dependent variable (y) at a given point.

• The slope of a trend line shows the average of the independent variable (x) over time.

• The slope of a trend line indicates the correlation between two variables without specifying direction.

What is the significance of the R-squared value in regression analysis?

• It measures the strength of the relationship between two independent variables.

• It indicates the proportion of variance in the dependent variable that can be explained by the independent variable.

• It is used to determine the sample size needed for a study.

• It represents the average of the residuals in a regression model.

What is the purpose of a scatter plot?

• To visually display the relationship between two variables and to identify any patterns or correlations.

• To create a bar graph of data points.

• To summarize data in a table format.

• To show the distribution of a single variable.