Exploring Scatter Plots and Trend Lines

What is primarily shown in the first quadrant of a scatter plot?

• Positive X and Y values

• No specific data trend

• Negative X and Y values

• Negative and positive Y values

What does a scatter plot with points moving from bottom left to top right indicate?

• Data inconsistency

• Positive correlation

• No correlation

• Negative correlation

When plotting a scatter plot, what represents the X and Y values?

• Speed and time respectively

• Temperature and altitude respectively

• Altitude and temperature respectively

• Time and speed respectively

What is the first step in creating a scatter plot from data?

• Plotting the points

• Labeling the axes

• Drawing the trend line

• Calculating the correlation

What type of correlation is indicated if the data points in a scatter plot trend downwards?

• Data error

• No correlation

• Negative correlation

• Positive correlation

What is the purpose of a trend line in a scatter plot?

• To predict future data points

• To separate different data sets

• To make the plot look organized

• To measure the plot area

How do you determine the slope of a trend line?

• Subtracting the Y values of any two points

• Adding the X values of any two points

• Dividing the change in Y by the change in X

• Multiplying the highest X and Y values

What does a positive correlation in data imply about the relationship between two variables?

• As one increases, the other also increases

• There is no relationship between the variables

• As one decreases, the other also decreases

• As one increases, the other decreases

Which scenario is an example of a causal relationship?

• More cars causing higher temperatures

• More books causing better health

• More loaves of bread causing more flour usage

• More firefighters causing more mailboxes

What does it mean if there is no causal relationship between two correlated variables?

• Changes in one variable predict changes in the other

• Both variables are independent of each other

• The correlation is coincidental and not causative

• One variable directly affects the other