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Chapter Two. Statistics and the Research Process. The Logic of Research. Chapter 2 - 2. Scientific Research. The goal of science is to understand the “laws of nature” We examine a specific influence on a specific behavior in a specific situation

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chapter two

Chapter Two

Statistics and the

Research Process

scientific research
Scientific Research

The goal of science is to understand the “laws of nature”

We examine a specific influence on a specific behavior in a specific situation

Then, we generalize back to the broader behaviors and laws with which we began

Chapter 2 - 3

samples and populations
Samples and Populations

The entire group of individuals to which a law applies is the population

A sample is a relatively small subset of a population that is intended to represent, or stand for, the population

The individuals measured in a sample are called the participants or subjects

Chapter 2 - 5

drawing inferences
Drawing Inferences

We use the scores in a sample to infer or to estimate the scores we would expect to find in the population.

Chapter 2 - 6

representativeness
Representativeness

In a representative sample, the characteristics of the sample accurately reflect the characteristics of the population.

Chapter 2 - 7

random sampling
Random Sampling

Randomsampling is a method of selecting a sample in which the individuals are randomly selected from the population.

Chapter 2 - 8

unrepresentative samples
Unrepresentative Samples

Random sampling should result in a sample that is representative of the population, but it is not foolproof

An unrepresentative sample can result in misleading evidence and wrong conclusions

Chapter 2 - 9

obtaining data
Obtaining Data

A variable is anything that, when measured, can produce two or more different values (scores). Some common variables are:

Age

Race

Gender

Intelligence

Personality type

Chapter 2 - 10

types of variables
Types of Variables

A quantitative variable indicates the amount of a variable that is present

A qualitative variable classifies an individual on the basis of some characteristic

Chapter 2 - 11

examining relationships
Examining Relationships

In a relationship, as the scores on one variable change, the scores on the other variable change in a consistent manner.

Chapter 2 - 12

strength of a relationship
Strength of a Relationship

The strength of a relationship is the degree of consistency in the relationship

A stronger relationship occurs when one group of similar Y values is associated with one X score and a different group of similar Y scores is associated with the next X score

Chapter 2 - 13

factors affecting strength
Factors Affecting Strength

A “weaker” relationship may be due to additional extraneous influences and/or individual differences

Individual differences refer to the fact no two individuals are identical

Chapter 2 - 14

graphing relationships
Graphing Relationships

Describe a relationship using the general format:

“Scores on the Y variable change as a function of changes in the X variable.”

The given variable in a study is the X variable.

Chapter 2 - 15

four sample graphs
Four Sample Graphs

A graph showing

a perfectly

consistent

association.

Chapter 2 - 16

four sample graphs17
Four Sample Graphs

A relationship

that is not

perfectly

consistent.

Chapter 2 - 17

four sample graphs18
Four Sample Graphs

A weak

relationship.

Chapter 2 - 18

four sample graphs19
Four Sample Graphs

No consistent

pattern.

Chapter 2 - 19

descriptive statistics
Descriptive Statistics

Descriptive statistics are procedures used for organizing and summarizing data.

What scores occurred?

What is the average or typical score?

Are the scores very similar to each other or very different?

Is a relationship present?

Chapter 2 - 21

inferential statistics
Inferential Statistics

Inferential statistics are procedures for deciding whether sample data accurately represent a particular relationship in the population

Inferential statistics allow us to make inferences about the scores and relationship found in the population

Chapter 2 - 22

statistics and parameters
Statistics and Parameters

A statistic is a number that describes a characteristic of a sample of scores

A parameter is a number that describes a characteristic of a population of scores

Chapter 2 - 23

research designs
Research Designs

A study’s design is the way the study is laid out

There are two major types of designs:

Experiments

Correlational studies

Chapter 2 - 25

experiments
Experiments

In an experiment, the researcher actively changes or manipulates one variable and then measures participants’ scores on another variable to see if a relationship is produced.

Chapter 2 - 26

the independent variable
The Independent Variable

The independent variable is the variable that is changed or manipulated by the experimenter

A condition is a specific amount or category of the independent variable that creates the specific situation under which participants are examined

Chapter 2 - 27

the dependent variable
The Dependent Variable

The dependent variable is used to measure a participant’s behavior under each condition of the independent variable

We apply descriptive statistics only to the scores from the dependent variable

Chapter 2 - 28

correlational studies
Correlational Studies

In a correlational study, we simply measure participants’ scores on two variables and then determine whether a relationship is present.

Chapter 2 - 29

causality
Causality

We cannot definitively prove the independent variable causes the scores on the dependent variable to change. It is always possible some other hidden variable is actually the cause.

Chapter 2 - 30

characteristics of variables
Characteristics of Variables

Two important characteristics of variables are

The type of measurement scale involved

Whether it is continuous or discrete

Chapter 2 - 32

measurement scales
Measurement Scales

There are four types of measurement scales:

A nominal scale does not indicate an amount; rather, it is used for identification, as a name.

An ordinal scale indicates rank order. There is not an equal unit of measurement separating each score.

Chapter 2 - 33

measurement scales cont d
Measurement Scales (cont’d)

An interval scale indicates an actual quantity and there is an equal unit of measurement separating adjacent scores. Interval scales do not have a “true” 0.

A ratio scale reflects the true amount of the variable that is present because the scores measure an actual amount, there is an equal unit of measurement, and 0 truly means that zero amount of the variable is present.

Chapter 2 - 34

discrete and continuous
Discrete and Continuous

Any measurement scale also may be either continuous or discrete

A continuous scale allows for fractional amounts and so decimals make sense

In a discrete scale, only whole-number amounts can be measured

Chapter 2 - 35

dichotomous variable
Dichotomous Variable
  • A dichotomous variable has only two possible categories or scores:
    • Male or female
    • Yes or no
    • Correct or incorrect

Chapter 2 - 36

slide38

Key Terms

  • as a function of
  • condition
  • continuous scale
  • correlational study
  • dependent variable
  • descriptive statistics
  • design
  • dichotomous variable
  • discrete scale
  • experiment
  • independent variable
  • individual differences
  • inferential statistics
  • interval scale
  • level
  • nominal scale
  • ordinal scale
  • parameter
  • participant
  • population

Chapter 2 - 38

Chapter 1 - 38

slide39

Key Terms (Cont’d)

  • ratio scale
  • relationship
  • sample
  • statistic
  • strength of a relationship
  • treatment
  • variable

Chapter 2 - 39

Chapter 2 - 39

Chapter 1 - 39