Stats: Chapter 1

population

The collection of all individuals or items under consideration in a statistical study.

Cluster Sampling

This method is used frequently when the members of the population are wide scattered geographically. This method works well if each cluster is representative of the population. 1. divide the population into groups (clusters) 2. obtain a simple random sample of the clusters 3. use all the members of the clusters obtained in step 2 as the sample

Stratified Random Sampling

Very useful when the population can be easily divided into subgroups called strata which are homogeneous. This method is often more reliable than cluster sampling. Using this method we are able to make conclusions for the complete population and for each individual strata in the population. 1. divide the population into subpopulations (strata) 2. from each stratum, obtain a simple random sample of size proportional to the size of the stratum; that is, the sample size for a stratum equals the total samle size times the stratum size divided by the population size. 3. use all the members obtained in step 2 as the sample

inferential statistics

consists of methods for drawing and measuring the reliability of conclusions about a population based on information obtained from a sample of the population

descriptive statistics

consists of methods for organizing and summarizing information

simple random sample

A sample obtained by simple random sampling.

simple random sampling

A sampling procedure for which each possible sample of a given size is equally likely to be the one obtained. Is the most natural and easily understood method of probability sampling.

Multistage Sampling

Most large-scale surveys combine one or more of simple random sampling, systematic random sampling, cluster sampling, and stratified sampling. Such multistage sampling is used frequently by pollsters and government agencies.

census

Obtaining information for the entire population of interest.

Systematic Random Sampling

One method that takes less effort to implement than simple random sampling. The results are comparable with simple random sampling unless there is some sort of cyclical pattern within the list of the members of the population. 1. divide the population size by the sample size and round the result down to the nearest whole number, m. 2. use a random-number table or a similar device to obtain a number, k, between 1 and m. 3. Select from the sample those membres of the population that are numbered, k, k+m, k+2m,....

designed experiment

Researchers impose treatments and controls and then observe characteristics and take measurements. (Can help establish causation). The data does not exist until someone does something (the experiment) that produces the data.

observational study

Researchers simply observe characteristics and take measurements, as in a sample survey. (Can only reveal association). Someone is observing data that already exists.

representative sample

Should reflect as closely as possible the relevant characteristics of the population under consideration.

sample

That part of the population from which information is obtained.

Two methods, other than census for obtaining information?

1. Sampling 2. Experimentation

What is Statistics?

1. facts or data, either numerical or nonnumerical, organized and summarized so as to provide useful and accessible information about a particular subject. 2. the science of organizing and summarizing numerical or nonnumerical information.

What are the two type of simple random sampling?

1. with replacement - a member of the population can be selected more than once 2. without replacement - a member of the can be selected at most once.