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
- analysis of variance
- also referred to as ANOVA; a method of testing whether the means of three or more populations are equal
The method is applicable if- all populations of interest are normally distributed,
- the populations have equal standard deviations, and
- samples (not necessarily of the same size) are randomly and independently selected from each population.
The test statistic for analysis of variance is the F ratio.
- one-way ANOVA
- a method of testing whether the means of three or more populations are equal; the method is applicable if
- all populations of interest are normally distributed,
- the populations have equal standard deviations,
- samples (not necessarily of the same size) are randomly and independently selected from each population, and
- there is one independent variable and one dependent variable.
The test statistic for analysis of variance is the F ratio
- variance
- mean of the squared deviations from the mean; the square of the standard deviation
For a set of data, a deviation can be represented as x – where x is a value of the data and is the sample mean. The sample variance is equal to the sum of the squares of the deviations divided by the difference of the sample size and 1.