Statistics

Cross-Sectional Study

"Snapshot" - data are collected at a single point in time.

Cross-Sectional Study Example

A Gastroenterologist surveys 130 of his patients six months after having gastric bypass surgery to determine the average amount of weight loss.

Population Parameter

A characteristic or measure of a population.

Meta-Analysis Example

A citizens watch committee studies three newspaper articles about crime prevention.

Longitudinal Study Example

A group of 220 patients is followed for 15 years in order to determine the long-term health effects resulting from gastric bypass surgery.

Meta-Analysis Example

A meteorologist studies five weather reports from hurricanes to compare for common factors.

Sample Statistic

A numerical measure that describes an aspect of a sample.

Cluster Sampling Example

A random number generator is used to choose ten cities. Political Strategist collects data from each person in these cities.

Inferential Statistic Example

A recent poll of 3517 luxury car owners in Michigan showed that the average price of a luxury car in the U.S. is $29,500.

Experimental Study

A study in which the researcher manipulates one of the variables and tries to determine how the manipulation influences other variables. Cause and effect.

Meta-Analysis (One Variable)

A study that compiles information from previous studies. One variable is examined over several studies.

Inferential Statistic Example

A survey of 3389 people revealed that 54% are self-conscious about their weight; therefore it can be assumed that 54% of the U.S. population are self-conscious about their weight.

Non-Sampling Error

An error that occurs from sources other than the construction of the sample; occurs when a subject lies when answering a survey

Sampling Error

An error that occurs when a sample somehow does not represent the target population; one way to avoid this is to choose a large enough sample size.

Participation Bias

Bias occurs when there is a problem with the participation or lack thereof, of those chosen for the study; a self-selected survey is prone to this.

Quantitative, Discrete, Interval data

Birth years of each person in your family

Longitudinal Study

Data gathered by following a particular group over a period of time.

Discrete Data

Data that can only take certain values. Usually counts like the number of pets you have. Also IQ's.

Continuous Data

Data that can take on any value. There is no space between data values for a given domain. Graphs are represented by solid lines. Data can be measured. Fahrenheit and Celsius temperatures.

Interval Data

Differences between values can be found, but there is no absolute 0. (Temp. and Time and IQ's) (Zero does not mean the absence of something)

Cluster Sampling

Divide population into clusters; each cluster is similar to entire population; randomly select whole clusters to sample

Simple Random Sampling

Each sample has an equal chance of being selected

Processing Error

Error that occurs from sources other than the construction of the sample.

Case Study Example

Fifteen cattle are selected and examined for signs of disease.

Descriptive Statistic

Gathers, sorts, summarizes, and displays data that have been collected. "Just the facts"

Case Study (Multiple Variables)

Looks at multiple variables that affect a single event.

Observational Study

Observes individuals and measures variables of interest but does not attempt to influence the responses. Data already there.

Researcher Bias

Occurs when a researcher influences the results of a study; one form of this bias is in the wording of survey questions a researcher has given to participants; occurs if a researcher intentionally chooses a favorable sample.

Ordinal Data

Qualitative data that can be ranked (meaningful order). (Excellent, Average, & Poor)

Nominal Data

Qualitative data which consists of names, labels, or categories.

Ratio Data

Quantitative data which have a specific unit of measure and a natural zero point. The full range of mathematical operations can be meaningfully applied. (Age, weight, height, Temperature in Kelvin)

Descriptive Statistic Example

The price of a car at the new car dealership in town is $28,400.

Inferential Statistic

Uses descriptive statistics to estimate population parameters

Simple Random Sampling Example

We interviewed a sample of 41 mothers of eighth graders from one middle school. These mothers were randomly selected from a list of 129 mothers provided by the principal of the school.