Statistics: Informed Decisions Using Data, Seventh Edition - Chapter 1: Data Collection

This set of vocabulary flashcards covers essential terminology from Chapter 1 regarding data collection, variable types, levels of measurement, sampling methods, bias, and experimental design.

Statistics

The science of collecting, organizing, summarizing, and analyzing information to draw conclusions or answer questions, as well as providing a measure of confidence in any conclusions.

Data

A fact or proposition used to draw a conclusion or make a decision that describes characteristics of an individual; a key aspect is that it varies.

Population

The entire group of individuals to be studied.

Individual

A person or object that is a member of the population being studied.

Sample

A subset of the population that is being studied.

Statistic

A numerical summary of a sample, such as the $46\%$ car ownership rate found in a sample of $100$ students.

Parameter

A numerical summary of a population, such as the $48.2\%$ car ownership rate for all students on a campus.

Descriptive Statistics

Consist of organizing and summarizing data through numerical summaries, tables, and graphs.

Inferential Statistics

Uses methods that take a result from a sample, extend it to the population, and measure the reliability of the result.

Variables

The characteristics of the individuals within the population.

Qualitative Variables

Also known as categorical variables, they allow for classification of individuals based on some attribute or characteristic.

Quantitative Variables

Provide numerical measures of individuals where values can be added or subtracted to provide meaningful results.

Discrete Variable

A quantitative variable that has either a finite number of possible values or a countable number of possible values (e.g., $0, 1, 2, 3$).

Continuous Variable

A quantitative variable that has an infinite number of possible values that are not countable, taking on every possible value between any two values.

Nominal Level of Measurement

A level of measurement where the values of the variable name, label, or categorize, but do not allow for a ranked or specific order.

Ordinal Level of Measurement

A level of measurement where values can be arranged in a ranked or specific order, such as a letter grade in a class.

Interval Level of Measurement

A level of measurement where differences in values have meaning, but a value of zero does not mean the absence of the quantity (e.g., Temperature).

Ratio Level of Measurement

A level of measurement where ratios of values have meaning and a value of zero means the absence of the quantity.

Response Variable

The variable in research for which we wish to determine if the value is affected by varying the explanatory variable (e.g., whether brain cancer was contracted).

Explanatory Variable

The variable that a researcher varies to determine its effect on the response variable.

Observational Study

Measures the value of the response variable without attempting to influence the value of either the response or explanatory variables.

Designed Experiment

A study where the researcher assigns individuals to groups, intentionally manipulates the value of an explanatory variable, and records the value of the response variable.

Confounding

Occurs in a study when the effects of two or more explanatory variables are not separated, making it difficult to determine the relation between a specific explanatory variable and the response variable.

Lurking Variable

An explanatory variable that was not considered in a study, but that affects the value of the response variable and is typically related to existing explanatory variables.

Confounding Variable

An explanatory variable that was considered in a study whose effect cannot be distinguished from a second explanatory variable in the study.

Cross-sectional Studies

Observational studies that collect information about individuals at a specific point in time, or over a very short period of time.

Case-control Studies

Retrospective studies where individuals who have certain characteristics are matched with those that do not by looking back in time or at existing records.

Cohort Studies

Prospective observational studies that identify a group of individuals (the cohort) and observe them over a long period of time while recording characteristics.

Census

A list of all individuals in a population along with certain characteristics of each individual.

Web Scraping

Also known as data mining, the process of extracting data from the Internet and transforming unstructured information into a structured format through parsing and reformatting.

Random Sampling

The process of using chance to select individuals from a population to be included in the sample.

Simple Random Sampling

Occurs when every possible sample of size $n$ from a population of size $N$ has an equally likely chance of occurring.

Frame

A list of all the individuals within the population used to number individuals for sampling.

Sample Without Replacement

A sampling method where an individual who is selected is removed from the population and cannot be chosen again.

Sample With Replacement

A sampling method where a selected individual is placed back into the population and could be chosen a second time.

Seed

An initial point used by a generator, such as a TI-84 Plus CE graphing calculator, to start creating random numbers.

Stratified Sample

Obtained by separating the population into nonoverlapping homogeneous groups called strata and then obtaining a simple random sample from each stratum.

Systematic Sample

Obtained by selecting every $k^{\text{th}}$ individual from the population, starting with a random number $p$ between $1$ and $k$.

Cluster Sample

Obtained by selecting all individuals within a randomly selected collection or group of individuals.

Convenience Sample

A sample in which the individuals are easily obtained and not based on randomness; results are generally suspect.

Voluntary Response Samples

A type of convenience sample where the individuals themselves decide to participate in a survey.

Multistage Sampling

A combination of sampling techniques, such as the two-stage process used by Nielsen Media Research involving stratified and simple random sampling.

Bias

Occurs if the results of a sample are not representative of the population.

Sampling Bias

Occurs when the technique used to obtain the individuals in the sample tends to favor one part of the population over another, often resulting in undercoverage.

Nonresponse Bias

Exists when individuals selected for the sample who do not respond have different opinions from those who do; can be improved with rewards or callbacks.

Response Bias

Exists when the answers on a survey do not reflect the true feelings of the respondent due to interviewer error, wording, or data-entry errors.

Open Question

A survey question that allows the respondent to choose their own response.

Closed Question

A survey question that requires the respondent to choose from a list of predetermined responses.

Nonsampling Errors

Errors resulting from undercoverage, nonresponse bias, response bias, or data-entry error; can be present in a complete census.

Sampling Error

Error that results from using a sample to estimate information about a population because a sample gives incomplete information.

Experiment

A controlled study conducted to determine the effect of varying factors on a response variable.

Treatment

Any combination of the values of the factors (explanatory variables) in an experiment.

Experimental Unit

Also called a subject, this is the person, object, or item upon which a treatment is applied.

Control Group

A group that serves as a baseline treatment used for comparison against other treatments.

Placebo

An innocuous medication, such as a sugar tablet, that looks, tastes, and smells like the experimental medication.

Single-blind Experiment

An experiment where the experimental unit does not know which treatment he or she is receiving.

Double-blind Experiment

An experiment where neither the experimental unit nor the researcher in contact with them knows which treatment is being received.

Replication

The application of each treatment to more than one experimental unit to ensure effects are not due to a single unit's characteristics.

Completely Randomized Design

An experimental design in which each experimental unit is randomly assigned to a treatment.

Matched-pairs Design

An experimental design in which units are paired based on relationship (e.g., twins or same person before/after) with only two levels of treatment.

Randomized Block Design

A design where experimental units are divided into homogeneous groups called blocks, and units within each block are randomly assigned to treatments.