Chapter 1: Introduction to Statistics and Research Design

Question 1

Descriptive Statistcs

Answer 1

Organize, summarize, and communicates a group of numerical observations; describe large amounts of data in a single number or in just a few numbers; Summarize numerical information about a sample

Question 2

Inferential Statistics

Answer 2

Uses a sample data to make general estimates about the larger population; Infers or makes an intelligent guess about an entire population

Question 3

Sample

Answer 3

Set of observations drawn from the population of interest; Draw conclusions about the broader population based on numerical information from a sample

Question 4

Population

Answer 4

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

Question 5

Variable

Answer 5

Any observation of a physical, attitudinal, or behavioral characteristic that can take on different values; can be abstract such as motivation, self-esteem, and attitudes

Question 6

Discrete Observations

Answer 6

Can take on only specific values; no other values can exist between these numbers; number of times participants get up early in a particular week, the only possible values would be whole numbers

Question 7

Continuous Observations

Answer 7

Can take on a full range of values (e.g. numbers out to several places); an infinite number of potential values exists; completion of tasks in 12.839 seconds; limited only by the number of decimal places we choose to use

Question 8

Nominal Variables

Answer 8

Used for observations that have categories or names as their values; always discrete (whole numbers); Gender (1=Male, 2=Female)

Question 9

Ordinal Variables

Answer 9

Observations that have rankings as their values; 1st, 2nd, or 3rd; Always discrete

Question 10

Interval Variables

Answer 10

Used for observations that have numbers as their values; the distance (or interval) between pairs of consecutive numbers is assumed to be equal;

Question 11

Number of times one has to get up early each week

Answer 11

Interval Variable because distance between numerical observations is assumed to be equal; Discreet Variable (Difference between 1 and 2 is the same as the difference between 5 or 6)

Question 12

Social Science Measures

Answer 12

Treated as interval measures but are also discrete, personality and attitude measures

Question 13

Studies that measure time and distance

Answer 13

Continuous, interval observations; ratio observations because zero has meaning for time and distance

Question 14

Ratio Variables

Answer 14

Variables that meet the criteria for interval variables but also have meaningful zero points; cognitive studies use ratio variable for reaction time; Time always implies a meaningful zero

Question 15

Stroop Test

Answer 15

Gives response times in whole numbers, although other versions are more specific and give response times to several decimal places

Question 16

Scale Variable

Answer 16

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

Question 17

Types of Variables used to quantify observations

Answer 17

Nominal - Always Discrete/Never Continuous
Ordinal - Always Discrete/Never Continuous
Interval - Sometimes Discrete/Sometimes Continuous
Ratio - Seldom Discrete/Almost always continuous

Question 18

Level

Answer 18

Discrete value or condition that a variable can take on

Question 19

Independent Variable

Answer 19

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

Question 20

Example of an Independent variable

Answer 20

If we are studying whether gender predicts one’s attitude about politics, the independent variable is gender with two levels, male and female

Question 21

Dependent Variable

Answer 21

The outcome variable that we hypothesize to be related to, or caused by, changes in the independent variable; variable that depends on the other

Question 22

Example of Dependent Variable and Independent Variable

Answer 22

Attitude about politics (Dependent variable)

Gender (Independent variable)

Question 23

Confounding Variable

Answer 23

Any variable that systematically varies with the independent variable so that we cannot logically determine which variable is at work; also called a confound

Question 24

Example of a confounding variable

Answer 24

Want to lose weight and start sing a diet drug and begin exercising at the same time; we cannot logically tell which one is responsible for any weight loss

Question 25

Reliability

Answer 25

Refers to the consistency of a measure

Question 26

Validity

Answer 26

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

Question 27

Why we conduct research

Answer 27

To see if an independent variable predicts a dependent variable

Question 28

Good Variable

Answer 28

Reliable (consistent over time) and valid (assesses what it is intended to assess

Question 29

Hypothesis testing

Answer 29

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

Question 30

Operational Definition

Answer 30

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

Question 31

Correlation

Answer 31

An association between two or more variables

Question 32

Random Assignment

Answer 32

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

Question 33

Experiment

Answer 33

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

Question 34

Between Groups Research Design

Answer 34

Participants experience one, and only one, level of the independent variable

Question 35

Within Groups research design

Answer 35

The different levels of the independent variable are experienced by all participants in the study, also called a repeated measures design.

Question 36

Outlier

Answer 36

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

Question 37

Outlier Analysis

Answer 37

Studies that examine obsevrations that do not fit the overall pattern of the data, in an effort to understand the factors that influence the dependent variable