Data Collection and Visualization Principles

Chapter 1: Introduction, Data Collection, and Experimental Design This chapter lays the groundwork

for the entire course, defining terminology and teaching how to gather reliable data.

Key Concepts:Population vs. Sample: The population is the entire group you want to study; a

sample is the subset you actually collect data from.Parameter vs. Statistic: A parameter describes

the population (e.g., population mean \(\mu \)); a statistic describes the sample (e.g.,

sample mean \(\={x}\)).Types of Variables: Quantitative (numerical measurements like height) and Categorical (groupings

or labels like eye color).Study Types: Observational studies merely observe existing conditions,

while experiments deliberately impose a treatment to determine cause and effect.Sampling Bias: Issues like