Chapter 1 Significance: How Strong is the Evidence?
1.1 Intro
- Statistics – Estimate broad populations
- No way to collect all information
- When is a sample Statistically Significant?
- Statistical Significance
- “Is our result unlikely to have occurred by random chance?”
- Helper vs. Hinderer
- Is 14/16 significantly higher than 8/16?
- Is 10/16 significantly higher than 8/16?
- Probability
- Long-run proportion of times an outcome from a random process occurs
- Probability Distribution- Pattern of long run outcomes
1.2 Definitions
- Sample: The set of observational units on which we collect data.
- Sample size: The number of observational units in the sample.
- Statistic: The number summarizing the result of the sample.
- Population: The complete collection of ALL elements that are of interest for a given problem.
- Parameter: The long-run numerical property of the process.
Population and Sample: Use Statistics (observed from sample) to Estimate the Parameter (population unknown value).
