Contents
- Preface
1Sampling and Data
- Introduction
- 1.1Definitions of Statistics, Probability, and Key Terms
- 1.2Data, Sampling, and Variation in Data and Sampling
- 1.3Frequency, Frequency Tables, and Levels of Measurement
- 1.4Experimental Design and Ethics
- 1.5Data Collection Experiment
- 1.6Sampling Experiment
- Key Terms
- Chapter Review
- Practice
- Homework
- Bringing It Together: Homework
- References
- Solutions
10Hypothesis Testing with Two Samples
- AAppendix A Review Exercises (Ch 3–13)
- BAppendix B Practice Tests (1–4) and Final Exams
- CData Sets
- DGroup and Partner Projects
- ESolution Sheets
- FMathematical Phrases, Symbols, and Formulas
- GNotes for the TI-83, 83+, 84, 84+ Calculators
- HTables
- Index
Key Terms
- normal distribution
- a continuous random variable (RV) where μ is the mean of the distribution and σ is the standard deviation; notation: X ~ N(μ, σ). If μ = 0 and σ = 1, the RV is called the standard normal distribution.
- standard normal distribution
- a continuous random variable (RV) X ~ N(0, 1); when X follows the standard normal distribution, it is often noted as Z ~ N(0, 1).
- z-score
- the linear transformation of the form z = ; if this transformation is applied to any normal distribution X ~ N(μ, σ), the result is the standard normal distribution Z ~ N(0, 1);
If this transformation is applied to any specific value x of the RV with mean μ and standard deviation σ, the result is called the z-score of x. The z-score allows us to compare data that are normally distributed but scaled differently.