Answer:
1. Statistical Inference
2. Variability.
3. Outlier.
4. Population.
5. Sample.
Explanation:
1. Statistical Inference: Reasoning from a sample to a population. For example, the average common entrance score of all examinees (population l) in New York city or a business that collects data from a random sample of 100 consumers and recorded whether they are male or female.
2. Variability: Successive observations of a system or phenomenon do not produce exactly the same result. For instance, the distribution having the same value of mean can have varying variability.
3. Outlier: An observation that differs considerably from the main body of the data. For example, in the following scores 1, 2, 3, 4, 50, 5, 60; both 50 & 60 is an outlier.
4. Population: The entire collection of objects or outcomes about which data are collected. For example, the number of new born babies in a hospital, the total number of football players in a soccer league.
5. Sample: A subset of the population containing the observed objects or outcomes and the resulting data from these objects or outcomes. For example, the average height of girls in a class having a population of 10 boys and 20 girls.