Chapter 1: Introduction to Statistics and Research Design Flashcards

1
Q

Descriptive Statistcs

A

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

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2
Q

Inferential Statistics

A

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

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3
Q

Sample

A

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

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4
Q

Population

A

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

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5
Q

Variable

A

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

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6
Q

Discrete Observations

A

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

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7
Q

Continuous Observations

A

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

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8
Q

Nominal Variables

A

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

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9
Q

Ordinal Variables

A

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

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10
Q

Interval Variables

A

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

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11
Q

Number of times one has to get up early each week

A

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)

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12
Q

Social Science Measures

A

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

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13
Q

Studies that measure time and distance

A

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

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14
Q

Ratio Variables

A

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

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15
Q

Stroop Test

A

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

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16
Q

Scale Variable

A

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

17
Q

Types of Variables used to quantify observations

A

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

18
Q

Level

A

Discrete value or condition that a variable can take on

19
Q

Independent Variable

A

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

20
Q

Example of an Independent variable

A

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

21
Q

Dependent Variable

A

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

22
Q

Example of Dependent Variable and Independent Variable

A

Attitude about politics (Dependent variable)

Gender (Independent variable)

23
Q

Confounding Variable

A

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

24
Q

Example of a confounding variable

A

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

25
Reliability
Refers to the consistency of a measure
26
Validity
Refers to the extent to which a test actually measures what it was intended to measure
27
Why we conduct research
To see if an independent variable predicts a dependent variable
28
Good Variable
Reliable (consistent over time) and valid (assesses what it is intended to assess
29
Hypothesis testing
Process of drawing conclusions about whether a particular relation between variables is supported by the evidence
30
Operational Definition
Specifies the operations or procedures used to measure or manipulate a variable
31
Correlation
An association between two or more variables
32
Random Assignment
Every participant in the study has an equal chance of being assigned to any of the groups, or experimental conditions
33
Experiment
Study in which participants are randomly assigned to a condition or level of one or more independent variables
34
Between Groups Research Design
Participants experience one, and only one, level of the independent variable
35
Within Groups research design
The different levels of the independent variable are experienced by all participants in the study, also called a repeated measures design.
36
Outlier
Extreme score that is either very high or very low in comparison with the rest of the scores in the sample
37
Outlier Analysis
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