Clearly indicate which variables you are using and how they are coded e.g., 1 = ?, 2 =
?, 3 = ?, etc. OR state 1 indicates a lower score and 10 indicates a higher score, etc.
3. ☐ Based on how your variables are coded, indicate whether each variable is quantitative
or categorical.
4. ☐ If you recode a variable you must discuss how you did that here.
5. ☐ Given the way your variables are coded, indicate what types of analysis will be
performed (e.g., crosstabulation, ANOVA, or correlation).
You MUST present your descriptive statistics and perform one statistical analysis (you will not
be given extra marks if you perform more than one statistical analysis).
You are limited to three possible techniques, and this decision is made by the variables that you
have selected.
• Crosstab (two categorical variables)
• Correlation (two quantitative variables)
• Comparing means (one categorical and one quantitative).
You MUST create your own tables.
You MUST also report the level of statistical significance in your tables and in the text.
• No asterisks (not statistically significant)
• One asterisk (significant at .05)
• Two asterisks (significant at .01)
• Three asterisks (significant at .001) You should create one table for your descriptive statistics, and one table for your statistical analysis.
Each table must also include the appropriate N value.
In your results section simply report your results as was done in class.
Remember to treat all ordinal variables (e.g., education) and Likert variables (e.g., strongly agree
to strongly disagree) as quantitative variables (thus they should be used in correlations and
ANOVA’s) – as long as they have at least 4 categories. Do NOT treat these variables as
categorical. In other words, these variables should not be used in crosstabulations.
Please verify that you have interpreted your results correctly. For example, many variables are
reverse coded (e.g., education). If your variables are reverse coded you MUST note the reverse
coding in your results table, and in your write-up.
In your tables report the mean category for ordinal variables–not the numerical values. For
example, if the mean for an ordinal variable is 2.1 and that corresponds with the category
“Agree” then you must put “Agree” as the mean category in the table, not the value 2.1
Take this example:
Suppose we are comparing males and females in terms of their scores on an attitudinal question
where 1= agree strongly, 2=agree, 3=disagree, and 4=disagree strongly.
Suppose also that the average score for males is 2.8 and the average score for females is 2.1. In
this case, the average category for both males and females is the same (even if the difference is
statistically significant). Thus, in your ANOVA Table you need list the average category for
each group as “Agree,” rather than the numbers (2.8 and 2.1).
In the text of the paper you can state that even though the average category for both groups is
“agree,” males are less likely to agree with the statement than females.
If you are using a categorical variable with many categories (e.g., religion and province) recode
them so that they have less than five categories. This will make the results less tedious and easier
to interpret.
Include your SPSS output at the very end of the paper.
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