**Core Concept**
The question pertains to statistical analysis in research, specifically the confidence interval (CI) and its calculation using the Z-score, which is a measure of the number of standard deviations from the mean.

**Why the Correct Answer is Right**
The Z-score is used to calculate the confidence interval (CI) in a normal distribution. The formula for the CI is given by: CI = mean ± (Z-score × standard deviation). In this case, the Z-score is given as 1.96, which corresponds to a 95% confidence level. This is because the Z-score is related to the area under the standard normal curve, and a Z-score of 1.96 corresponds to the area between the mean and 95% of the distribution. The 95% confidence level is often used as a standard in research, implying that if the true population mean were to be measured multiple times, the calculated CI would contain the true mean 95% of the time.

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because it does not specify the confidence level associated with the Z-score. While a Z-score of 1.96 is commonly used for a 95% confidence level, it is not the only possible Z-score for different confidence levels.
**Option B:** This option is incorrect because it does not provide any information about the confidence level or the Z-score.
**Option C:** This option is incorrect because it is a placeholder and does not provide any information about the confidence level or the Z-score.

**Clinical Pearl / High-Yield Fact**
The Z-score is a crucial concept in statistical analysis, and understanding its relationship with the confidence interval is essential for interpreting research results. A commonly used Z-score for a 95% confidence level is 1.96, which corresponds to the area between the mean and 95% of the distribution.

**Correct Answer: D. 95%**