

Connections
• 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.
• Inference
 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
inference.
 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 zscores. Remember: their sample may not be
normal, but the sampling distribution of their sample mean or
proportion is normal under Central Limit Theorem.
