Research Methods Exam 1

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Non-Scientific Methods of Acquiring Knowledge

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Method of Tenacity(Superstition)

Method of Authority

Method of Intuition

Empirical Method (direct observation/experience)

Rational Method (logical reasoning)

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The Scientific Method

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an approach to acquiring knowledge that involves formulating specific questions, then systematically finding answers

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Induction/ Inductive Reasoning

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Involves using relatively small set of specific observations to form a general statement about a larger set of observations

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Deduction/ Deductive reasoning

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Uses general statement to reach a conclusion about specific examples

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What are the 3 important principles of the scientific method?

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It Is:

1)Empirical

2)public

3)objective

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What are the 4 elements of a good Hypothesis?

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It is:

1)Logical

2)Refutable

3)Testable

4)Positive (it affirms the existence of something)

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Applied Research

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Research studies that are intended to answer practical questions or solve practical problems

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Basic Research

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Research studies that are intended to answer theoretical questions or gather knowledge simply for the sake of new knowledge

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Primary Source

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A firsthand report of observations or research results written by the individuals who actually conducted the research and made the observations

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Secondary source

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A description or summary of another person's work, written by someone who did not participate in the research or observations being discussed.

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Clinical Equipose

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The ethical issue requiring clinicians to provide the best possible treatment for their patients, thus limiting research to studies that compare equally preferred treatments

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Passive Deception (Omission)

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The withholding or omitting of info; the researcher intentionally does not tell participants some info about the study

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Active Deception (Comission)

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The presenting of misinformation about the study to participants.

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Informed Consent

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The ethical principle requiring the investigator to provide all available info about a study so the participant can make an informed, rational decision about whether to participate in the study

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Debriefing

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A post-experimental explanation of the purpose of the study; Given after a participant has completed the study, especially if deception was used.

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Confidentiality

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The practice of keeping strictly secret and private the info or measurements obtained from an individual during a research study

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Anonymity

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The practice of ensuring that an individual's name is not directly associated with the info or measures obtained from that individual

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Fraud

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The explicit effort of a researcher to falsify or misrepresent data

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Replication

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The repetition of a research study using the same basic procedures used in the original; it either supports the original by duplicating the results or casts doubt by demonstrating that the original results are not easily repeated

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Plagiarism

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The representation of someone else'e ideas or words as one's own.

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Hypothetical Construct

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Hypothetical attributes or mechanisms that help explain and predict behavior in a theory

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Operational Definition

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A procedure for measuring and defining a construct; Specifies a measurement procedure (set of operations) for measuring an external observable behavior and uses the resulting as a definition and measurement of a hypothetical construct

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Validity

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The degree to which the study accurately answers the questions it was intended to answer

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Face Validity

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Concerns the superficial appearance, or face value of a measurement procedure; Does the technique look like it measures the variable it claims to measure?

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Concurrent Validity

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Validity demonstrated when scores obtained from a new measure are directly related to scores obtained from a more established measure of the same variable

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Predictive Validity

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Validity demonstrated when scores obtained from a measure accurately predict behavior according to a theory

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Construct Validity

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Demonstrated when the scores obtained from a measurement behave exactly the same as the variable itself

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Convergent Validity

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Demonstrated by a strong relationship between the scores obtained from 2 different methods of measuring the same construct

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Divergent Validity

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Demonstrated using 2 different methods to measure 2 different constructs. Convergent validity must be shown for each construct, then there should be little or no relationship between the scores obtained for the 2 different constructs when measured by the same method

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Reliability

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The degree of stability or consistency of measurements

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Test-Retest Reliabilty

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Established by comparing the scores obtained from 2 successive measurements of the same individuals and calculating a correlation between the 2 sets of scores

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Parallel-Forms Reliability

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Established by comparing scores obtained by using 2 alternate versions of a measuring instrument to measure the same individuals and calculating a correlation between the 2 sets of scores

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Inter-Rater Reliablity

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The degree of agreement between 2 observers who simultaneously record measurements of the behaviors

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Split-Half Reliability

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Obtained by splitting the items on a questionnaire or test in half, computing a separate score for each half and then calculating the degree of consistency between the 2 scores for a group of participants

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What are the 4 Scales of Measurement?

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1) The Nominal Scale

2)The Ordinal Scale

3) Interval Scale

4)Ratio Scale

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Nominal Scale

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Categories represent qualitative difference in the variable being measured; categories have different names that are not related in any way (eg. Name, Occupation, Address)

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Ordinal Scale

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Categories have different names and are organised sequentially (1st, 2nd, 3rd)`

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Interval Scale

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The categories are organised sequentially and all categories are the same size. The zero point is arbitrary and does not indicate an absence of the variable being measured (eg. temperature,)

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Ratio Scale

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The categories are sequentially organised, all categories are the same size, the zero point is absolute or non-arbitrary and indicates a complete absence of the variable being measured (eg Pounds, Time etc)

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Artifact

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A non-natural feature accidentally introduced into something being observed; an external factor that may influence or distort the measurements

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Experimenter Bias

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Occurs when the measurements obtained in a study are influenced by the experimenter's expectations or personal beliefs regarding the outcome of the study

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How can experimenter bias be reduced?

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Through:

1)Single-Blind research

2)Double-Blind Research

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Reactivity

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Occurs when participants modify their natural behavior in response to the fact that they are participating in a research study or the knowledge that they are being measured

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Demand Characterstics

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Any of the potential cues or features of a study that 1)Suggest to the participants what the purpose and hypothesis is and 2)influence the participants to respond to behave in a certain way

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What are the 2 general categories of statistical techniques?

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1)Descriptive statistics

2)Inferential statistics

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Descriptive Statistics

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Methods that help researchers organize, summarize and simplify results obtained from research studies (eg graph, table, average scores)

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Inferential Statistics

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Methods that use the results obtained from samples to help make generalizations about populations

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Statistic

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A summary value that describes a sample

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Parameter

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A summary value that describes a population

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Central Tendency

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A statistical measure that identifies a single score that defines the center of a distribution. The goal is to identify the value that is most representative or typical of the entire group

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What are the 3 measures of central tendency?

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1)Mean

2)Median

3)Mode

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Mean

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Obtained by adding the individual scores, then dividing the sum by the number of scores.

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Median

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Measures central tendency by identifying the score that divides the distribution in half (Arrange scores in order, median is the one in the middle)

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Mode

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Measure central tendency by identifying the most frequent occurring score in the distribution

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Variability

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A measure of the size of the spread of score in a distribution

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What are 2 methods of measuring variability?

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1)Standard Deviation

2)Variance

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Standard Deviation

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A measure of variability that describes the average distance from the mean; obtained by taking the square root of the variance

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Variance

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A measure of variability obtained by computing the average squared distance from the mean.

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Sampling Error

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The naturally occurring difference between a sample statistic and the corresponding population parameter; i.e the sample does not produce a perfectly accurate picture of its population

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Hypothesis Test

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An inferential statistical procedure that uses sample data to evaluate the credibility of a hypothesis about a population; determines whether the results are statistically significant

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What are the 5 basic elements of a Hypothesis Test?

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1)The Null Hypothesis

2) The Sample Statistic

3)Standard Error

4)The Test Statistic

5) The Alpha Level (Level of Significance)

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Null Hypothesis

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A statement about the population(s) or treatments being studied that says that there is no change, no difference, no effect or no relationship; i.e what would the parameters be if nothing happened

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Standard Error

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A measure of the average or standard distance between a sample statistic and the corresponding population parameter

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Test Statistic

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A summary value computed in a hypothesis test to measure the degree to which the sample data are in accord with the null hypothesis; ie the actual difference in data & hypothesis divided by the difference expected by chance

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The Alpha Level/ Level of Significance

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is the criterion for statistical significance that defines the maximum probability that the research result was obtained simply by chance; criterion for evaluating the significance of the test statistic

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(Statistically) Significant Result

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Means that it id extremely unlikely that the research result was obtained simply by chance.

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What are the 2 types of errors that can be made in hypothesis testing?

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1) Type I Error

2) Type II Error

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Type I Error

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Occurs when the researcher finds evidence for a significant result when, in fact, there is no effect or relationship in the population. (Consequence: false report)

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Type II Error

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Occurs when sample data do not show evidence of a significant effect when, in fact, a real effect does exist in the population

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Standardized Distribution

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is composed of scores that have been transformed to create predetermined values for the mean and standard deviation; used to make dissimilar distributions comparable