Chapter 1 Vocabulary

Chapter 1:

© Rita Marie O’Brien Chapter 1 1 Chapter 1 Statistics is the science of collecting, organizing, analyzing, and interpreting data in order to make decisions. Data consists of information coming from observations, counts, measurements, or responses. The singular for data is datum. Data Set is a whole collection of data.

Two types of statistics::

© Rita Marie O’Brien Chapter 1 2 Two types of statistics: Descriptive is the branch of statistics that involves the organization,summarization, and display of data. (describes) Inferential is the branch of statistics that involves using a sample to draw conclusions about a population. (infers)

Definitions:

© Rita Marie O’Brien Chapter 1 3 Definitions Probability is the chance of an event occurring. Population is the collection of all outcomes, responses, measurements, or counts that are of interest. Sample is a subset of a population. Variable is an attribute or characteristic that can assume different values.

Variables are the factors you want to study.:

© Rita Marie O’Brien Chapter 1 4 Variables are the factors you want to study . Independent variable is manipulated by the researcher. Dependent variable is the outcome of the independent variable. Confounding variable influences the dependent variable but cannot be separated from the independent variable Qualitative Variables consists of attributes, labels, or non-numerical entries.(categories) Quantitative Variables consists of numerical measurements. (ranked)

Random Variables are selected by chance. :

© Rita Marie O’Brien Chapter 1 5 Random Variables are selected by chance. A random variable is discrete if it has a finite or countable number of possible outcomes that can be listed.( countable ) A random variable is continuous if it has a infinite number of possible outcomes, represented by an interval on the number line. ( measured )

Five types of Samples::

© Rita Marie O’Brien Chapter 1 6 Five types of Samples : In a random sample , each member has an equal chance of being selected. In a convenience sample , simply use any members of a population that are readily available. This method is likely to produce biased results.

Slide 7:

© Rita Marie O’Brien Chapter 1 7 Five types of Samples : 3. In a stratified sample , a population is divided into at least two different subsets called strata . That share a similar characteristic. A sample is the randomly selected from each. The defining characteristic can be gender, age or even political preference. Using a stratified sample insures each segment of the population is represented.

Slide 8:

© Rita Marie O’Brien Chapter 1 8 Five types of Samples : 4. In a cluster sample , divide a population into groups, called clusters , then select all of the members of one or more, but not all, of the clusters. This technique is often used because of practical or economic restrictions, but data collected may be less reliable than when a random sample is used.

Slide 9:

© Rita Marie O’Brien Chapter 1 9 Five types of Samples : 5. In a systematic sample , a population is ordered in some way and then the members of the population are selected at regular intervals.(every k th number) The selection process can start at any randomly chosen point. An advantage of the method is that it is easy to use.