Getting Started 
Misconception/Error The student is unable to use technology to correctly compute a correlation coefficient. 
Examples of Student Work at this Level The student:
 Indicates that he or she does not know how to use technology to calculate a correlation coefficient.
 Computes something other than the correlation coefficient, such as the line of best fit and reports its slope as the correlation coefficient.Â

Questions Eliciting Thinking How did you enter the data?
Which option did you choose in order to determine your result?
Is the slope of the line of best fit the same as the correlation coefficient? 
Instructional Implications Review the meaning of the correlation coefficient. Emphasize that the correlation coefficient is a measure of the degree to which two variables are linearly related. Be sure to discuss the range of possible values, the difference between a negative and positive correlation, and values that indicate strong, moderate, and weak relationships. Guide the student to interpret correlation coefficients in the context of data rather than giving a generic characterization such as â€śa strong positive relationship.â€ť Model applying this kind of language to the specific variables under study. For example, say, â€śA correlation coefficient of 0.9299 indicates that that there is a strong, positive relationship between height and foot length. As height increases, foot length increases.â€ť
Provide instruction on using technology to calculate the correlation coefficient. Provide additional opportunities to calculate and interpret correlation coefficients in the context of the data. 
Making Progress 
Misconception/Error The student does not offer a clear and complete interpretation. 
Examples of Student Work at this Level The student correctly reports the correlation coefficient, but cannot clearly interpret it. For example, the student:
 Does not refer to the context of the data and only says that it indicates a strong positive relationship.
 Provides an incomplete or incorrect interpretation.

Questions Eliciting Thinking Do you expect the coefficient to be positive or negative?
What would a correlation coefficient equal to one mean?
What would a correlation coefficient equal to negative one mean?
Can you explain the correlation coefficient in the context of the variables? What does this correlation coefficient say about the association between height and foot length? 
Instructional Implications Provide feedback concerning any errors made in reporting the correlation coefficient. Review the meaning of the correlation coefficient. Emphasize that the correlation coefficient is a measure of the degree to which two variables are linearly related. Be sure to discuss the range of possible values, the difference between a negative and positive correlation, and values that indicate strong, moderate, and weak relationships. Guide the student to interpret correlation coefficients in the context of data rather than giving a generic characterization such as â€śa strong positive relationship.â€ť Model applying this kind of language to the specific variables under study. For example, say, â€śA correlation coefficient of 0.9299 indicates there is a strong, positive relationship between height and foot length. As height increases, foot length increases.â€ť
Provide additional opportunities to calculate and interpret correlation coefficients in the context of the data. 
Got It 
Misconception/Error The student provides complete and correct responses to all components of the task. 
Examples of Student Work at this Level The student correctly finds the correlation coefficient, , and interprets it as indicating there is a strong positive linear relationship between height and foot length. In other words, as height increases, foot length increases.

Questions Eliciting Thinking What would you expect a graph of this data to look like?
Would the slope of the line of best fit be positive or negative? 
Instructional Implications Ask the student to graph the data given in the table and use technology to find the equation of the line of best fit. Ask the student to use the equation to make predictions about the foot length at heights not given in the table. Then ask the student to consider if it makes sense to use the equation to determine the foot length of a female. 