This document defines key terms related to sampling methods in statistics. It explains that a population is the entire group being studied, while a sample is a subset of the population that is surveyed to make inferences. There are different types of samples, including random samples where each member has an equal chance of being selected, stratified samples which are selected randomly from subgroups, and convenience samples which are easiest to reach. The document also notes that biased samples do not accurately represent the full population.
1. Inferences:
Lesson 1: Samples and Surveys
EQ:
How can I identify sampling methods?
How can I recognize biased samples
7.SP.1 and 7.SP.2
2. Getting Started.
Statistics deals with collecting, organizing and interpreting data.
A survey is a method of collecting information. The group being
studied in the population. Sometimes the population is very
large. To save time and money, part of the group, called a
sample is surveyed.
3. How you ever heard the Family Feud?
The Family Feud is a game that uses surveys to determine
what a survey of 100 people would say on a topic.
4. Let’s Learn Some New Words Before our
Vocabulary Quiz
Population – the entire group being considered for a survey.
Sample – A part of the population being surveyed.
Biased sample – A sample that does not accurately represent the population.
Random sample – A sample in which each member of the populatarion has and equal
chance of being selected.
Systematic sample – A sample of a population that has been selected according to a rule or
a formula.
Stratified sample – A sample of a population that has been selected at random form
randomly chosen subgroups.
Convenience sample – A sample of a population that has been selected because they were
easiest to reach.
Voluntary-response sample- A sample of a population that has been selected because the
embers choose to be in the sample.
