• 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

1/22

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;

22 Cards in this Set

  • Front
  • Back

Define "statistics"

Statistics is the science of data which involves collecting, classifying, summarizing, organizing, analyzing, presenting, and interpreting numerical information.

What are some application areas in which statistics is involved?

Economics, Engineering, Sports, Business, and etc.

What are the two processes of statistics?

1. describing sets of data


2. drawing conclusions (making estimates, decisions, predictions, etc. about sets of data based on sampling).

What are two types of statistical methods?

descriptive and inferential statistics

Define "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.

Define "inferential statistics"

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

What is the difference between descriptive and inferential statistics?

descriptive involves collecting, presenting, characterizing, and summarizing data. Overall purpose is to describe data.



inferential involves estimation and hypothesis testing. Overall purpose is to make decisions about population characteristics.

What are the fundamental elements of statistics?

1. Experimental (or observational) unit


2. Population


3. Variable


4. Sample

What is a experimental (or observational) unit?

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

How would you define population in statistics?

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

What is a variable?

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

define a "sample" in statistics?

A subset of the units of a population.

List two fundamental elements

Statistical Inference and Measure of Reliability

Define statistical inference & measure of reliability

statistical inference- estimate or prediction or generalization about a population based on information contained in a sample.



measure of reliability- statement (usually quantitative) about the degree of uncertainty associated with a statistical inference.

What are 4 elements of descriptive statistical problems?

1. The population or sample of interest


2. One or more variables that are to be investigated


3. Tables, graphs, or numerical summary tools


4. Identification of patterns in the data.

What are the 5 elements of inferential statistical problems?

1. The population of interest


2. One or more variables 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 reliability for the inference

What are two types of data in statistics?

Quantitative (measurements that are recorded on a naturally occurring numerical scale).



Qualitative (or categorical data are measurements that cannot be measured on a natural numerical scale; they can only be classified into one group of categories).

What is a designed experiment?

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

List and define two types of "samples" in statistics

Representative sample- exhibits characteristics typical of those possessed by the population of interest.



Random sample- sample selected from the population of n experimental units in such a way that every different sample of size n has an equal chance of selection.

What is the importance of selection?

How a sample is selected from a population is of vital importance in statistical inference because the probability of an observed sample will be used to infer the characteristics of the sampled population.

Define 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.

What are some examples of nonrandom sample errors?

Selection bias, non-response bias, and measurement error.