Bivariate Data

What is the purpose of calculating the correlation coefficient?

• To measure the average of a dataset.

• To quantify the degree of linear relationship between two variables.

• To determine the mode of a set of numbers.

• To calculate the variance of a dataset.

What is the role of regression analysis in bivariate data?

• To model the relationship between two variables and predict outcomes.

• To calculate the mean of two variables.

• To determine the correlation coefficient between two variables.

• To visualize the data in a scatter plot.

How can you determine the strength of a relationship in bivariate data?

• By analyzing the mean of the data

• By using the correlation coefficient and the scatter plot's pattern

• By calculating the median of the data

• By observing the range of the data

What is correlation in the context of bivariate data?

• Correlation measures the strength and direction of the relationship between two variables.

• Correlation is the process of collecting data from two different sources.

• Correlation indicates the average of two variables over time.

• Correlation is a method used to predict future outcomes based on past data.

How do you interpret a scatter plot with a downward trend?

• A downward trend in a scatter plot indicates a positive correlation between the two variables.

• A downward trend in a scatter plot indicates no correlation between the two variables.

• A downward trend in a scatter plot indicates a negative correlation between the two variables.

• A downward trend in a scatter plot indicates that one variable causes the other to decrease.

What does a correlation coefficient of -1 indicate?

• A perfect positive linear relationship between two variables.

• No linear relationship between two variables.

• A perfect negative linear relationship between two variables.

• A weak negative linear relationship between two variables.

What does a correlation coefficient of 1 indicate?

• A perfect positive linear relationship between two variables.

• No relationship between the two variables.

• A perfect negative linear relationship between two variables.

• A weak positive relationship between two variables.

What is the formula for the line of best fit in linear regression?

• y = mx + b

• y = ax^2 + bx + c

• y = m + b

• y = mx^2 + b

What is the significance of outliers in bivariate data?

• Outliers have no effect on correlation and trend lines.

• Outliers can significantly affect the correlation and trend line, potentially skewing the results.

• Outliers are always removed from data analysis.

• Outliers only affect univariate data.

What is the difference between causation and correlation?

• Causation indicates a relationship without implying direct influence.

• Correlation implies that one variable directly affects another.

• Causation implies that one variable directly affects another, while correlation indicates a relationship without implying direct influence.

• Correlation and causation are the same concept.