What This Document Is
This handout, “Kissing Right?”, presents a real-world statistical study investigating a curious human behavior: whether people tend to lean to the right or left when kissing. It uses the observed data from a study of kissing couples to introduce and practice foundational concepts in statistical inference, specifically hypothesis testing regarding population proportions. The document frames the investigation around a biologist’s conjecture about early embryonic development influencing later behaviors.
Why This Document Matters
This handout is designed for students in Applied Statistics for the Life Sciences (STAT 218) at Cal Poly San Luis Obispo. It’s used to apply theoretical statistical concepts to a tangible, and somewhat unexpected, example. Students will use this material to build skills in formulating statistical questions, interpreting data, and evaluating evidence. It’s particularly relevant when learning about sample proportions, null distributions, and assessing the strength of evidence against a hypothesis.
Common Limitations or Challenges
This handout focuses on *setting up* a statistical test, not completing it. It provides the initial data and guiding questions, but doesn’t fully resolve the hypothesis test. Students will need to apply additional statistical tools and calculations (not shown here) to reach a conclusion. It also assumes prior knowledge of basic statistical concepts like sample proportions and null distributions.
What This Document Provides
This handout includes:
* A description of the observational study conducted on kissing couples.
* The raw data regarding the number of couples observed and the direction they leaned.
* A series of conceptual questions designed to guide students through the initial stages of hypothesis testing. These questions prompt students to consider the sample proportion, its relationship to a potential population proportion, and the role of variability.
* Hints to help students think through the concepts.
This preview does *not* include: the completed hypothesis test, calculations of standard errors or p-values, or a definitive conclusion regarding the researcher’s conjecture. It also does not provide a full explanation of the underlying statistical theory.
