Chapter 1 Flashcards

terms and definitions for chap. 1 of An intro to statistics and research design

1
Q

Descriptive statistic

A

organizes, summarizes, and communicates a group of numerical observations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

inferential statistic

A

uses sample data to make a general estimates about the larger population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

sample

A

is a set of observations drawn from the population of interest

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

population

A

includes all possible observations about which we’d like to know something

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

variable

A

is any observation of a physical, attitudinal, or behavioral characteristic that can take on different values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

discrete observations

A

can take on only specific values (e.g. whole numbers); no other values can exist between these numbers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

continuous observation

A

can take on a full range of values (e.g. numbers out to several decimal places); an infinite number of potential values exists.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

nominal variable

A

is a variable used for observations that have categories, or names, as their values.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

ordinal variable

A

is a variable used for observations that have rankings (i.e. 1st, 2nd, 3rd,…) as their values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

interval variable

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

ratio variable

A

is a variable that meets the criteria for an interval variable but also has a meaningful zero point.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

scale variable

A

a variable that meets the criteria for an interval variable or a ratio variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

level

A

is a discrete value or condition that a variable can take on

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

independent variable

A

has at least two levels that we either manipulate or observe to determine its effects on teh dependent variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

confounding variable

A

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.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

reliability

A

refers to the consistency of a measure

17
Q

validity

A

refers to the extent to which a test actually measures what it was intended to measure

18
Q

hypothesis testing

A

is the process of drawing conclusions about whether a particular relation between variables is supported by the evidence

19
Q

operational definition

A

specifies the operations or procedures used to measure or manipulate a variable

20
Q

correlation

A

is an association between two or more variables

21
Q

random assignment

A

every participant in a study has an equal chance of being assigned to any of the groups , or experimental conditions, in the study

22
Q

experiment

A

is a study in which participants are randomly assigned to a condition or level of one or more independent variables

23
Q

between-groups research design

A

participants experience one, and only one, level of independent variable

24
Q

within-groups research design

A

the different levels of the independent variables are experienced by all participants in the study, also called repeated-measures design.

25
Q

outlier

A

is an extreme score that is either very high or very low in comparison with the rest of the scores in the sample

26
Q

outlier analysis

A

studies examine observations that do not fit the overall pattern of the data in an effort to understand the factors that influence the dependent variable