Stats Chapter 1

Front 1

statistics

Back 1

a set of mathematical procedures for organizing, summarizing, and interpreting information

Front 2

Stats Process

Back 2

1) the big research question
2) how to pose it
3) leads to a particular kind of data
4) organize it
5) Analyze it
6) Interpret and present

Front 3

population

Back 3

the set of all the individuals of interest in a particular study

Front 4

sample

Back 4

set of individuals selected from a population, usually intended to represent the population in a research study

Front 5

variable

Back 5

a characteristic or condition that changes or has different values for different individuals

Front 6

Data (plural)

Back 6

measurements or observations

Front 7

data set

Back 7

a collection of measurements or observations

Front 8

datum (singular)

Back 8

a single measurement or observation and is commonly called a score or raw score

Front 9

parameter

Back 9

a value, usually a numerical value, that describes a population. A parameter is usually derived from measurements of the individuals in the population.

Front 10

statistic

Back 10

a value, usually a numerical value, that describes a sample. A statistic is usually derived from measurements of the individuals in the sample.

Front 11

Descriptive statistics

Back 11

statistical procedures used to summarize, organize, and simplify data.

Front 12

Inferential statistics

Back 12

consist of techniques that allow us to study samples and then make generalizations about the populations from which they were selected.

Front 13

Sampling error

Back 13

the naturally occurring discrepancy, or error, that exists between a sample statistic and the corresponding population parameter.

Front 14

correlational method

Back 14

two different variables are observed to determine whether there is a relationship between them.

Front 15

The Experimental Method

Back 15

one variable is manipulated while another variable is observed and measured. To establish a cause-and-effect relationship between the two variables, an experiment attempts to control all other variables to prevent them from influencing the results.
1. Manipulation
2. Control

Front 16

independent variable

Back 16

the variable that is manipulated by the researcher. In behavioral research, the independent variable usually consists of the two (or more) treatment conditions to which subjects are exposed. The independent variable consists of the antecedent conditions that were manipulated prior to observing the dependent variable.

Front 17

dependent variable

Back 17

the variable that is observed to assess the effect of the treatment.

Front 18

control condition

Back 18

Individuals in a control condition do not receive the experimental treatment. Instead, they either receive no treatment or they receive a neutral, placebo treatment. The purpose of a control condition is to provide a baseline for comparison with the experimental condition.

Front 19

experimental condition

Back 19

Individuals in the experimental condition do receive the experimental treatment.

Front 20

quasi-independent variable.

Back 20

In a nonexperimental study, the “independent variable” that is used to create the different groups of scores

Front 21

Constructs

Back 21

internal attributes or characteristics that cannot be directly observed but are useful for describing and explaining behavior.

Front 22

operational definition

Back 22

identifies a measurement procedure (a set of operations) for measuring an external behavior and uses the resulting measurements as a definition and a measurement of a hypothetical construct. Note that an operational definition has two components: First, it describes a set of operations for measuring a construct. Second, it defines the construct in terms of the resulting measurements.

Front 23

discrete variable

Back 23

consists of separate, indivisible categories. No values can exist between two neighboring categories

Front 24

continuous variable

Back 24

there are an infinite number of possible values that fall between any two observed values. A continuous variable is divisible into an infinite number of fractional parts.

Front 25

Real limits

Back 25

the boundaries of intervals for scores that are represented on a continuous number line. The real limit separating two adjacent scores is located exactly halfway between the scores. Each score has two real limits

Front 26

upper real limit

Back 26

at the top of the interval

Front 27

lower real limit

Back 27

at the bottom of the interval

Front 28

nominal scale

Back 28

consists of a set of categories that have different names. Measurements on a nominal scale label and categorize observations, but do not make any quantitative distinctions between observations.

Front 29

ordinal scale

Back 29

consists of a set of categories that are organized in an ordered sequence. Measurements on an ordinal scale rank observations in terms of size or magnitude.

Front 30

interval scale

Back 30

consists of ordered categories that are all intervals of exactly the same size. Equal differences between numbers on a scale reflect equal differences in magnitude. However, the zero point on an interval scale is arbitrary and does not indicate a zero amount of the variable being measured.

Front 31

ratio scale

Back 31

an interval scale with the additional feature of an absolute zero point. With a ratio scale, ratios of numbers do reflect ratios of magnitude.

Front 32

Different kinds of research studies

Back 32

1. Descriptive (observational)
2. Correlational (relationships)
3. Experimental (cause and effect)

Front 33

Logic of a true experiment

Back 33

1. create two conditions
2. make them identical except for the hypothesized variable
3. If differences were observed it must be because of the causal variable
4. Why? it was the only difference

Front 34

Hallmarks of a true experiment

Back 34

1. Manipulation
2. Random Assignment
3. Experimental control
*without these three things we cannot conclude that x causes y

Front 35

Population

Back 35

Posses all the characteristics that we want to study

Front 36

Sample

Back 36

A subset of the population (usually random)

Front 37

Parameter

Back 37

Any number that describes a population

Front 38

Statistic

Back 38

Any number that describes a sample

Front 39

Measurement

Back 39

The way I measure my variables determines what I can do with them

Front 40

Persuasion

Back 40

Ex 1
Were you persuaded? yes no
Ex 2
To what extent do you agree with the message?
1 2 3 4 5

Front 41

Scales of measurement

Back 41

1. Nominal
2. Ordinal
3. Interval
4. Ratio

Front 42

Nominal Data

Back 42

Qualitative
Names or identities
(discrete)
ex. names, SS#s, word categories

Front 43

Ordinal data

Back 43

Variable reflects differences in magnitude, but only in term of order
(discrete)
ex. Rank in race (1st, 2nd, 3rd)

Front 44

Interval data

Back 44

The nature of a numeric scale
Equal distance between intervals reflect equal distance in magnitude
(continuous)
ex. temp in fahrenheit

Front 45

Ratio data

Back 45

Equal distance between intervals reflect equal differences in magnitude
There is a true zero point
(either, treated as continuous)
ex. temp in kelvin