SOCR Events May2008 C9 S1

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(New page: == SOCR May 2008 Event - Analyze bivariate data using linear regression methods== ===Fit regression lines to pairs of numeric variables and calculate the means a...)
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===Fit regression lines to pairs of numeric variables and calculate the means and standard deviations of the two variables and the correlation coefficient, using technology===  
===Fit regression lines to pairs of numeric variables and calculate the means and standard deviations of the two variables and the correlation coefficient, using technology===  
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* Copy the first 200 measurements of the [[SOCR_Data_Dinov_020108_HeightsWeights | Human Height and Weight Dataset]] into the [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analysis (Simple Linear Regression)].
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<center>[[Image:SOCR_Events_May2008_C7_S1_Dinov_020808_Fig2.jpg|500px]]
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[[Image:SOCR_Events_May2008_C9_S1_Dinov_020808_Fig2.jpg|500px]]</center>
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* Map the Heights and Weights columns to the X and Y variables.
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<center>[[Image:SOCR_Events_May2008_C9_S1_Dinov_020808_Fig3.jpg|500px]]</center>
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* Click CALCULATE and see the output numerical results (in the Results tab) and the graphical outputs (in the Graphs tab).
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<center>[[Image:SOCR_Events_May2008_C9_S1_Dinov_020808_Fig4.jpg|500px]]
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[[Image:SOCR_Events_May2008_C9_S1_Dinov_020808_Fig5.jpg|500px]]</center>
===Compute predictions of y-values for given x-values using a regression equation, and recognize the limitations of such predictions===
===Compute predictions of y-values for given x-values using a regression equation, and recognize the limitations of such predictions===

Revision as of 00:40, 9 February 2008

Contents

SOCR May 2008 Event - Analyze bivariate data using linear regression methods

Fit regression lines to pairs of numeric variables and calculate the means and standard deviations of the two variables and the correlation coefficient, using technology

  • Map the Heights and Weights columns to the X and Y variables.
  • Click CALCULATE and see the output numerical results (in the Results tab) and the graphical outputs (in the Graphs tab).

Compute predictions of y-values for given x-values using a regression equation, and recognize the limitations of such predictions

Compute and use the standard error for regression

References



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