CORRELATION ACTIVITIES



CORRELATION EXPLORATIONNAME: __________________________________S.ID.8 Compute and interpret the correlation coefficient. 551439276174Data Set A00Data Set AS.ID.D.9 Distinguish between correlation and causation.Focus Question: Does increased consumption of ice cream cause more people to drown? Data set A is more strongly correlated than Data B. What do you think that means? 531986234942Data Set B0Data Set BThe linear regression function on a calculator will calculate the correlation coefficient for you.Make sure the calculator’s diagnostic function is turned on and find “r” the correlation coefficient.CATALOG (above zero) → Diagnostic On→ enter (twice)…the screen should say DONEEnter the x-coordinates of each data set as L1 and the y-coordinates as L2. Run linear regression and write down the r-value. 38554353135565xy1123353.5647xy1123353.56471134583118951xy1625.53544.554xy1625.53544.55448260-1270xy162434465463xy1624344654633442487594xy1123364365xy11233643653375859781xy1626354354xy162635435433664158666xy1123324556xy11233245561297477768540500What do you notice? What is important to notice?Graph the data shown in the table. Example A only; Example B has been graphed for you. Describe the relationship between the variables. For example, “As number of years of post-secondary school increase, salaries increase.” Describe the correlation as strong positive, weak positive, weak negative or strong negative. Guess the correlation coefficient.Determine if there is a causal relationship between the two variables. For example, does increased consumption of ice cream cause more people to drown? Of course not. 3778898130163Describe the relationship: 0Describe the relationship: -120073173182Statistics for one yearconsumption of margarinelbs. per persondivorce rate in Maine# per thousand8.2574.76.54.65.34.45.24.344.14.64.24.54.23.74.1Statistics for one yearconsumption of margarinelbs. per persondivorce rate in Maine# per thousand8.2574.76.54.65.34.45.24.344.14.64.24.54.23.74.1Example A: 2276764159558consumption of margarinelbs. per persondivorce rate in Maine# per thousand00consumption of margarinelbs. per persondivorce rate in Maine# per thousand2686974486065528938687620029014883810026877829721340042907203609600282632728806~~~~3163455132781515Guess the correlation coefficient: r = _____Is there a causal relationship between eating margarine and getting divorced? -120073118630# days absent in one semesterGPA03.533.053.013.872.423.813.682.552.6# days absentGPA00# days absent in one semesterGPA03.533.053.013.872.423.813.682.552.6# days absentGPA498538546328Describe the relationship: 0Describe the relationship: Example B: 2627745962312424center135428003135746126076003145559845120029133801446070040824725749700358740448318004895273163426004119245646600463267115470900281679223784~~~~Guess the correlation coefficient: r = _____Is there a causal relationship between days absent and GPA? (adapted from Spurious Correlations, .)3725379000Example C: Is there a correlation between consumption of ice cream and deaths due to drowning? Describe the association. Does eating ice cream cause people to drown?Of course not! What could be a third, “lurking variable” that might explain why these two quantities appear to be linked? SUMMARY: What is a correlation? What are some quantities that are correlated? What does the value of the correlation indicate? How are correlation and causation related? types of correlationstrong negative weak negativeno correlationweak positivestrong positive25226031026600250245299168001870482461860011410723229900391222920720067448040694676744805104517CHECK FOR UNDERSTANDING:Make up your own scenario that would have a negative correlation. Make up some data that would have a correlation coefficient between -0.5 and -0.75.Show it has a negative correlation in the graph. Make sure to label and scale your axes.Write a sentence to describe the relationship between the variables.Calculate the correlation coefficient.-207010217805 ................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download