• Shuffle
    Toggle On
    Toggle Off
  • Alphabetize
    Toggle On
    Toggle Off
  • Front First
    Toggle On
    Toggle Off
  • Both Sides
    Toggle On
    Toggle Off
  • Read
    Toggle On
    Toggle Off
Reading...
Front

Card Range To Study

through

image

Play button

image

Play button

image

Progress

1/27

Click to flip

Use LEFT and RIGHT arrow keys to navigate between flashcards;

Use UP and DOWN arrow keys to flip the card;

H to show hint;

A reads text to speech;

27 Cards in this Set

  • Front
  • Back

Statistics

The science of data; this involves collecting, classifying, summarizing, organizing, analyzing, presenting, and interpreting numerical information.

Descriptive Statistics

Utilizes numerical and graphical methods to look for patterns in a data set, to summarize the information revealed in a data set, and to present that information in a convenient form.

Inferential Statistics

Utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data.

Experimental (Observational) Unit

An object (e.g. person, thing, transaction, or event) about which we collect data.

Population

A set of units (usually people, objects, transactions, or events) that we are interested in studying.

Each set of data includes ______ the units in the population.

All

Variable

A characteristic or property of an individual experiment (observational) unit in the population.

Measurement

The process used to assign numbers to variables of individual population units.

Census

When a measure of a variable has been made for every unit of a population.

Sample

A subset of the units of a population.

Statistical Inference

An estimate, prediction, or some other generalization about a population based on information contained in a sample.

Reliability

How "good" the inference is.

Measure of Reliability

Accompanies an inference separates the science of statistics from the art of fortune telling; a statement (usually quantitative) about the degree of uncertainty associated with a statistical inference.

Four Elements of Descriptive Statistical Problems

1. The population or sample of interest.


2. One or more variables (characteristics of the population or sample units) that are to be investigated.


3. Tables, graphs, or numerical summary tools.


4. Identification of patterns in the data.

Five Elements of Inferential Statistical Problems

1. The population of interest.


2. One or more variables (characteristics of the population units) that are to be investigated.


3. The sample of population units.


4. The inference about the population based on information contained in the sample.


5. A measure of the reliability of the inference.

Quantitative Data

Measurements that are recorded on a naturally occurring numerical scale.

Qualitative (Categorical) Data

measurements that cannot be measured on a natural numerical scale; they can only be classified into one of a group of categories.

Data collection comes from 3 different sources. Name them:

1. Published Source


2. Designed Experiment


3. Observational Study (survey)

Designed Experiement

A data collection method where the researcher exerts full control over the characteristics of the experimental units sampled. These experiments are assigned the treatment and an untreated (control) group.

Observational Study

A data collection method where the experimental units are observed in their natural setting. No attempt is made to control the characteristics of the experimental units sampled (i.e. opinion polls, surveys).

Survey

Where the researcher samples a group of people, asks one or more questions, and records the responses.

Representative Sample

Exhibits characteristics typical of those possessed by the target population.

Random Sample

Consists of "n" experimental units and is a sample selected from the population in such a way that every different sample of size "n" has an equal chance of selection.

Statistical Thinking

Involves applying rational thought and the science of statistics to critically assess data and inferences. Fundamental to the thought process is that variation exists in populations of data.

Selection Bias

Results when a subset of the experimental units in the population is excluded so that these units have no chance of being selected in the sample.

Non-Response Bias

Results when the researchers conducting a survey or study are unable to obtain data on all experimental units selected for the sample.

Measurement Error

Refers to inaccuracies in the values of the data recorded. In surveys, this kind of error may be due to ambiguous or leading questions and the interviewer's effect on the respondent.