Terms

Match each of the terms on the left with its definition on the right. Click on the term first and then click on the matching definition. As you match them correctly they will move to the bottom of the activity.

1.1 The Two Branches of Statistics

Question

descriptive statistic
inferential statistic
sample
population
The population includes all possible observations about which we'd like to know something. (p. 2)
A descriptive statistic organizes, summarizes, and communicates a group of numerical observations. (p. 2)
A sample is a set of observations drawn from the population of interest. (p. 2)
An inferential statistic uses sample data to make general estimates about the larger population. (p. 2)

1.2 How to Transform Observations into Variables

Question

variable
discrete observation
continuous observation
nominal variable
ordinal variable
interval variable
ratio variable
A ratio variable is a variable that meets the criterion for an interval variable but also has a meaningful zero point. (p. 5)
A discrete observation can take on only specific values (e.g., whole numbers); no other values can exist between these numbers. (p. 4)
An interval variable is a variable used for observations that have numbers as their values; the distance (or interval) between pairs of consecutive numbers is assumed to be equal. (p. 4)
A continuous observation can take on a full range of values (e.g., numbers out to several decimal places); an infinite number of potential values exists. (p. 4)
A variable is any observation of a physical, attitudinal, or behavioral characteristic that can take on different values. (p. 4)
An ordinal variable is a variable used for observations that have rankings (i.e., 1st, 2nd, 3rd) as their values. (p. 4)
A nominal variable is a variable used for observations that have categories, or names, as their values. (p. 4)

1.3 Variables and Research

Question

scale variable
level
independent variable
dependent variable
confounding variable
reliability
validity
Validity refers to the extent to which a test actually measures what it was intended to measure. (p. 8)
Reliability refers to the consistency of a measure. (p. 8)
A dependent variable is the outcome variable that we hypothesize to be related to or caused by changes in the independent variable. (p. 7)
A level is a discrete value or condition that a variable can take on. (p. 7)
A confounding variable is any variable that systematically varies with the independent variable so that we cannot logically determine which variable is at work; also called a confound. (p. 7)
An independent variable has at least two levels that we either manipulate or observe to determine its effects on the dependent variable. (p. 7)
A scale variable is a variable that meets the criteria for an interval variable or a ratio variable. (p. 7)

1.4 Introduction to Hypothesis Testing

Question

hypothesis testing
operational definition
correlation
random assignment
experiment
between-groups research design
within-groups research design
Hypothesis testing is the process of drawing conclusions about whether a particular relation between variables is supported by the evidence. (p. 9)
An experiment is a study in which participants are randomly assigned to a condition or level of one or more independent variables. (p. 11)
An operational definition specifies the operations or procedures used to measure or manipulate a variable. (p. 10)
A correlation is an association between two or more variables. (p. 10)
With random assignment, every participant in a study has an equal chance of being assigned to any of the groups, or experimental conditions, in the study. (p. 11)
With a within-groups research design, all participants in the study experience the different levels of the independent variable; also called a repeated-measures design. (p. 13)
With a between-groups research design, participants experience one and only one level of the independent variable. (p. 12)