• Exploratory Data Analysis
- Confidence intervals and inference help students use data
to just answer that simple investigative question that they may have
developed about a particular population. This should reference back to
the first unit of the course.
- In order to evaluate whether assumptions hold, need to look
at shape, center, spread of sample distribution.
- Confidence intervals help us make inference about a
population using just a single sample. Just as the last unit discussed,
it is important to reiterate that we just need one sample to make
- Confidence intervals rely on sampling distributions and the
Central Limit Theorem (if assumptions are met), so it is important to
show students how these concepts all relate.
- For assumptions to be met, we need to follow good data
collection practices to obtain a random sample.
- If the Central Limit Theorem applies, students will need to
recall normal models and z-scores. Remember: their sample may not be
normal, but the sampling distribution of their sample mean or
proportion is normal under Central Limit Theorem.