For each of the following variables:

• YEARofBIRTH transformed into a new variable called . To do this you will need to use the Command. Hint codes 9998 and 9999 are missing value codes so you should exclude them from the calculations with the command at the bottom of the calculator dialogue boxes. You might even want to assign these codes as missing values for YEARofBirth in your data set before you begin the analysis.
  ces08_CPS_G3
  ces08_MBS_H2
  • ces08_MBS_I12
  • ces08_MBS_I13A

  Provide the values for the most appropriate measure of central tendency and measure of dispersion or spread. Once again, before conducting your analysis you should ensure that you filter out the cases for each variable that having missing values, such as refused to answer, no answer, and don't know.

  Question:

  Return to the variable AGE that you have created in question 2. Assume that the cases are "normally distributed" for this variable. If they were normally distributed what proportion of the cases for which we have data would have an AGE less than 25?

  Question:

  Identify and set as "missing values" in your data set the appropriate values for each variable required in the following pairs:

  • ces08_MBS_I10A by ces08_MBS_I12
  • ces08_MBS_I10C by ces08_MBS_I12

  Create a Scatterplot for each set of variables and calculate the Pearson's "r".

  Now do a regression analysis for each pair.

  What can you say about the association between the variables in each pair revealed by the "r" statistic and the relationship between the variables in each pair which is revealed by the regression analysis. What conclusions might you be tempted to draw about Canadian politics as a result of this analysis?

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