To read a crosstabulation, follow these three steps: (1) determine if the result is statistically significant; if it is, then (2) interpret the pattern in the table; if not, stop; After you interpret the pattern (if the table is reliable), think about how the independent variable, in the columns, might be related to the dependent variable, in the rows.
Step 1.
Compare the value of "p" for Chi-square with the
conventional criterion, 0.05, or 5%.
If you are challenged by
decimal numbers, here is a simple technique for comparing values. Take
the value of "p" and mulitply by 1,000. To get the result, move the
decimal three places to the right, adding zeros if needed. For
example, if p = 0.014, we would end up with 14. If p = 0.11, we would
get 110. If p = 0.0057, we would get 5.7 . Next, do the same for the
criterion, 0.05. This will always result in 50. Finally, compare the
modified value of p with the modified criterion. For example, for p =
0.014, we have 14 compared to 50. Since 14 is less than 50, this
result would be reliable. For p = 0.11, we have 110 compared to
50. Since 110 is greater than 50, this result is not reliable. For p =
0.0057, we have 5.7 compared to 50. Since 5.7 is less than 50, this
result is reliable.
Step 2.
Compare the column percents across each row. If the
percents are consistently different, the independent variable is
related to the dependent variable.
Step 3.
Interpret the results from a social scientific
perspective. Remember, the pattern describes general tendencies, or
probabilities, rather than particular cases.