To answer this question, we use the Chi-Square test (X^2 test) for statistical significance.
The first step is to identify the observed X^2 value, which is provided as 1.61.
Next, we assess this observed value against the significance level value, which in this case is 3.84. The significance level value also referred to as the critical value, is used to determine whether there is a significant difference between the observed and expected data.
Typically, if the X^2 observed value is greater than the significance level value, we conclude that there is a significant discrepancy between the observed and expected values. Conversely, if the X^2 observed value is less than the significance level value, this indicates that there is likely no significant difference between the observed and expected data.
Since 1.61, the observed X^2 value, is smaller than 3.84, the significance level value, we can reasonably state that there is no significant difference between the observed and expected values.
Hence the answer is c) No difference.