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Types of probability sampling

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Simple random - simplest and quickest Systematic - if used on a randomly ordered frame, results in truly random sample Stratified random -random sampling within all subgroups Cluster - random sampling within known clusters

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Nonprobability sampling

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Does not rely on random selection Weakens sample to population representativeness Used when other techniques will not result in an adequate or appropriate sample Used when researchers desire participants with special experiences.

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Nonprobability sampling techniques

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Convenience sample (not as effective) Volunteer sample (can create a bias) Inclusion/exclusion sample Snowball or network sample (people referring each other) Purposive sample (has a purpose) Quota sample (must have a certain amount)

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Sample size

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Number of people/units for whom you need to collect data Determined prior to selecting sample Less than the number you ask to participate The larger the sample relative to the population, the less error or bias

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What is a research hypotheses for quantitative research

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Educated guess or presumption based on literature. States the nature of the relationship between two or more variables. Predicts the research outcome. Research study designed to test the relationship described in the hypothesis.

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Directional hypothesis

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Precise statement indicating the nature and direction of the relationship/difference between Ex.) As a person practices public speaking more, the level of communication apprehension decreases.

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Nondirectional hypothesis

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States only that relationship/differences will occur Ex.) Personality and communication apprehension are related

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Assessing Hypothesis

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Simply stated? Single sentence? At least two variables? Variables clearly stated? is the relationship/difference precisely stated? Testable?

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Null Hypotheses

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Implicit complementary statement to the research hypothesis States NO RELATIONSHIP/DIFFERENCE exists between variables Statistical test performed on the null Assumed to be true until support for the research hypothesis is demonstrated

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A variable

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Element that is identified in the hypothesis or research question Property of characteristic of people or things that varies in quality or magnitude Must be identified as independent or dependent

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Independent Variables

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Manipulation or variation of this variable is the CAUSE of change in other variables

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Dependent variables

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The variable that is influenced or changed by the independent variable Also called outcome variable The variable of primary interest Research question/hypothesis describes, explains, or predicts changes in it

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Reliability and validity

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Reliability = consistency in procedures and in reactions of the participants Validity = truth ~Does it measure what it was intended to measure? ~~Invalid research (iPad adoption in Lafayette, measured in upper Lafayette) When reliability and validity are achieved, data are presumed to be free from systematic errors

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Social learning theory

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Human behavior is caused by their observation

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Nominal variable

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Variables that are "named", i.e. classified into one or more qualitative categories that describe the characteristic of interest

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Ordinal Variable

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Variables that have an inherent order to the relationship among the different categories Stage of cancer education level

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Interval

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Variable that have constant, equal distances between values, but the zero point is arbitrary Intelligence Pain level

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Ratio

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Variables have equal intervals between values, the zero point is meaningful Weight Pulsrate

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Mean

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Arithmetic mean or average Most sensitive to extreme scores Remember formula M = Σ(X)/N

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Median

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Middle of all scores on one variable

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Mode

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Score or scores that appear most often

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Bell curve

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A theoretical distribution of scores Majority of cases distributed around the peak in the middle Progressively fewer cases moving away from the middle Symmetrical -one side mirrors the other Mean median and mode have the same value

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Skewed distributions

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Positive (mean is greater than median and mode, very few high scores) and negative (mean is less than median and mode, very few low scores)

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Central tendency

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Mean, median and mode

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Dispersion

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Dispersion describes the spread of scores from the point of central tendency.

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Descriptive statistics

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Are the number of cases, central tendency and dispersion. They are used by researchers to describe variables. Used in statistical tests to analyze differences and relationships between variables

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Cases

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may be people, speaking turns, episodes

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Standard deviation (sd)

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If sd = 0, all scores are the same Larger the sd, the more the scores differ from the mean Formula SD=√Σ(X-M)^2/N -1 Σ = sum of X = individual score M = mean of all scores N = Sample size

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Measures of dispersion

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Describes the variability or spread of scores Should be reported with mean Range (highest to lowest score) Standard deviation

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Significance level

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The researcher sets the significance level, or p, for each statistical test The degree of error the researcher finds acceptable in a statistical test An estimate of what would happen if the study were actually repeated many times Generally .05 is accepted level If P> .05, the finding is nonsignificant If p is <_ .05, the finding is significant or real

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Hypothesis test

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Hypothesis states the expected relationship or difference between two or more variables Findings for alternative hypothesis is reported Experimental Hys/Null is statistically tested. Act of decision making based on the significance level. Decision based on comparison between p set before study to p produced by statistical test.

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Error in hypothesis testing

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Type 1 error - falsely reject the null Type 2 error - false rejection to experimental hypothesis

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Why Qualitative Research

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Effective in capturing complexity of communication phenomena Sensitive to social construction of meaning Emphasizes communication environment of interactants

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Aims of Qualitative

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Aims for SUBJECTIVITY Allows interactants' voices to be heard Preserves the form and content of interaction DISCOURSE is the data So, it is an INDUCTIVE analysis

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Mutual simultaneous shaping (qualitative)

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Everything influences everything else Emphasis on PROCESS and the HOLISTIC FRAME OF INTERACTION Plausible explanations built on what is OBSERVED Allows for MULTIPLE INTERPRETATIONS (reflects reality and creates social understanding of meaning)

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Difference between quantitiative - Qualitative

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Uses numbers - Uses detailed descriptions Participants randomly selected - Participants selected purposely Removes some level of contextuality - Deeply contextualized Relies on formal logic - Interpretive frame

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Generalizability

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extending findings to similar situations or similar people Extent to which conclusions developed from data collected from sample can be extended to its population Sample is representative to the degree that all units had same chance for being selected Representative sampling eliminates selection bias Representativeness can only be assured through random sampling

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Possibility of Error

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expected to occur; researchers use valid and appropriate techniques to help minimize it

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Evidence

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Based on data

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Skepticism

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researchers do not rely on what appears to be obvious

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Measurement and observation

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identifying and capturing the phenomenon

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Public Record

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available to anyone; not proprietary research

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Heuristic

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findings from one study lead to more questions for the next study

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Replicable

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conducting the same or similar study in different settings and with different participants

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Objectivity

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requirement of researcher to minimize personal bias

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Self-correcting

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researchers should continuously consider how to improve their procedures

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Explore all possible explanations

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for propositions and results

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Testable

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can be investigated

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Theory

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Set of concepts, definitions, and propositions that presents a systematic view of the phenomena Developed and tested over time Attempts to explain and predict phenomena Research should be theoretically driven or aid in the creation of theory

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Social science methods

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Look for patterns of communication behavior

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Empirical

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verify through observations or experiences

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Quantitative methods

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Relies on numerical measurement

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Qualitative methods

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Researcher is the primary observer

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The scientific approach

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Research follows traditions & procedures 1. Start with an interesting question 2. Formulate a hypothesis or research question 3. Use reason and experience to refine the hypothesis or research question 4. Conduct the observation, measurement, or experiment 5. Analyze and interpret the data * Introduction -> Literature Review -> Method -> Results -> Discussion.

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Choice and Role of Methodology

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Methodological tools for different purposes Content of research question or hypothesis drives selection of the methodological tool A method is only useful if it helps answer the research question or hypothesis

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Reasoning

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Deductive Inductive

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Deductive

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A type of logic in which one goes from a general statement to a specific instance. Example: All men are mortal. (major premise) Socrates is a man. (minor premise) Therefore, Socrates is mortal. (conclusion) The above is an example of a syllogism.

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Inductive

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A type of logic going from a series of specific cases to a general statement. Example: There are a series of numbers: 3, 7, 11, 15, 19, 23, (?) What are the next one?

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Research Question and Hypothesis

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Research Question (RQ): General Question Hypothesis: - States the nature of the relationship between two or more variables; - Proposition that a research want to test the relationship described in the hypothesis, - H testing answers to the RQ

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Evaluating your RQ and H

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Academically Worthy? Clearly stated? Specific enough? Each one asks only one question? Communication orientation? Biased? Can it be observed or measured? Time and resources? (Doable?)

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Theory research link

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Theory -provides patterns for interpreting data -links one study to another -provides a framework for understanding how communication concepts and issues are important helps us interpret the meaning of research findings Scientific inquiry is a process of developing and testing theory Process is not always linear Meaningful inquiry drives theory or is theory-driven Multiple studies used to develop or challenge theory

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Researcher has two broad ethical responsibilities

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Scientific responsibility - Knowledge Building The researcher's relationship to participants - Why?

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Ethical questions in planning research

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What are the benefits of this study? How will the consent of participants be gained? How will confidentiality/anonymity be handled? Are there potential physical or psychological harms? How will the researcher's role affect the study? Is researcher capable of conducting the study?

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The Belmont Report

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Guidelines adopted by federal departments and agencies Three ethical principles 1. Beneficence 2. Respect for persons 3. Justice

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Beneficence

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The well-being of participants is protected Participants protected from harm Researcher must maximize possible benefits Benefits to participants must outweigh risks

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Respect for persons

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Treat individuals as capable of making decisions - Participants must feel free to volunteer; no coercion Protecting those not capable of making their own decisions

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Justice

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Issues of fairness All participants treated equally Selection of participants - Am I conveniently selecting one group of participants because they are Easily available? In a position making it difficult to say no? In a position in which they can be manipulated into participating?

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Institutional review board

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University Institutional Review Board - Also called IRB or Human Subjects Review Determines if rights and welfare of research participants are adequately protected in research design Submit proposal before any data are collected

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IRB proposals

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Research questions or hypotheses Brief review of literature Description of how participants are recruited/selected Informed consent Research methods How benefits are maximized, risks minimized Anonymity & confidentiality Investigator's background

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Informed consent

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- It must be given to participants any time data are collected from them Obligations and responsibilities for the researcher Voluntary participation Written in a manner participants can understand - clear and accurate

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Application of descriptive statistics

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Reported in methods section of research report Mean, sd, range, and n should be reported for each variable Frequencies - the number of times a particular value of a variable occurs Percentages - often used to describe characteristics or attributes of participants

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Population

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all units (people or things) possessing the attributes and characteristics of interest Choose the dimensions or characteristics meaningful to the hypothesis or research question Must be at least one common characteristic among all members of a population Must develop procedure to ensure representative sampling

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Sampling frame

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subset of units that have a chance to become part of the sample

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Sample

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subset of a population Researchers study the sample to make generalizations back to the population

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Probability sampling

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The probability of any unit being included in the sample is known and equal When probability for selection is equal, selection is random Also known as random sampling Sampling error will always occur

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The Classical experiment

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Researcher controls Treatment (with stimulus) & control groups - based on theory Random sample Random assignment of participants to conditions - ensures participants in each condition are equivalent before any treatment Manipulation checks How the independent variable is presented.

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Types of design

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Pretest-Posttest Experimental Design Posttest Experimental Design Longitudinal Experimental Designs

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Evaluating Experimental Design (strengths)

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Researcher controls manipulation of IV and random assignment to condition Assumes that any effect on DV is the cause of the IV Precision

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Evaluating Experimental Design (Limitations)

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Not all communication can be studied using experiments Other external influence may be the cause of DV change - Contamination effect May not reflect reality

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Quasi experiments

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Does not meet all of the requirements necessary for controlling the influence of extraneous variables. Most common criteria not met is random assignment. While you cannot infer cause and effect Posttest, pretest-posttest, and longitudinal designs can be used Includes field experiments in which communication is studied in context

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Study groups

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Groups or subjects not randomly assigned e.g., sample of convenience May not have a comparison group Typical of clinical research e.g., within subjects repeated measures

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Descriptive designs

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Also called cross-sectional or non-experimental studies Researcher does not control manipulation of IV Participants not randomly assigned to conditions Predictor and criterion are better labels for IV and DV as they do not imply causality "What are people's attributes for the disclosure and non-disclosure of privacy information?"

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Researcher effects & procedural bias

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Introduced in interaction with participants Similarity of researcher to participants How researcher communicates to participants Researcher unknowingly encourages desired responses Demand characteristics created when topic has socially desirable elements Use research protocol to detail procedural steps

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