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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Statistics and the
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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
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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
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We use the scores in a sample to infer or to estimate the scores we would expect to find in the population.
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In a representative sample, the characteristics of the sample accurately reflect the characteristics of the population.
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Randomsampling is a method of selecting a sample in which the individuals are randomly selected from the population.
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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
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A variable is anything that, when measured, can produce two or more different values (scores). Some common variables are:
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A quantitative variable indicates the amount of a variable that is present
A qualitative variable classifies an individual on the basis of some characteristic
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In a relationship, as the scores on one variable change, the scores on the other variable change in a consistent manner.
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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
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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
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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.
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A graph showing
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that is not
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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?
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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
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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
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A study’s design is the way the study is laid out
There are two major types of designs:
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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.
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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
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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
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In a correlational study, we simply measure participants’ scores on two variables and then determine whether a relationship is present.
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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.
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Two important characteristics of variables are
The type of measurement scale involved
Whether it is continuous or discrete
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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.
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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.
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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
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