Scientific Method Steps 1. A. 6. 1. B. Observation 2. 5. 3. 4.

Experimental Research An experiment is a scientific investigation that sets out to determine the cause and effect of two or more variables. A “good” experiment… 1. manipulates the independent variable 2. compares the groups in terms of the dependent variable 3. assures that only the IV causes the changes in the DV if this is accomplished then the experiment has internal validity 4. minimizes confounding variables any variable that varies along with the IV 5. uses randomization 6. uses experimenter control

Independent or Dependent? Independent Variable What the experimenter manipulates The “cause” of the experiment It is “independent” of all other variables Dependent Variable What the experimenter measures The “effect” of the experiment It “depends” on the Independent Variable

Independent Variable: Factors and Levels  The Experimental Design depends on two things:      The Number of Independent Variables (or Factors) used One Factor is nice and simple Two or more become Factorial Analysis    The Number of Levels within each Independent Variable

Operational Definition A definition of a variable that allows it to be concretely measured. A variable is an Abstract Concept It must be translated into a Concrete Form so it can be measured and studied empirically Helps to successfully communicate ideas to others Often a variety of measures are used

Dependent Variable Ceiling Effect Floor Effect should be sensitive enough to detect differences between groups Ceiling Effect IV seems to have no effect only because participants quickly reach the maximum performance level Floor Effect IV seems to have no effect only because the task is so difficult that participants cannot perform well

Types of Data Categorical, Qualitative Variables: Nominal Ordinal e.g., “yes/no”; “male/female” Ordinal e.g., “first, second, third”; “gold, silver, bronze” Continuous, Quantitative Variables: Interval e.g., “temperature” Ratio e.g., “exam scores”; “GPA”

Independent or Between-Subjects Requirements: Each level of each independent variable has different subjects. participants are randomly assigned to the different groups random assignment prevents any systematic biases   Advantages: minimizes order effects minimizes demand characteristics is the easiest to statistically analyze. Drawbacks: requires many subjects less statistical power takes more time Control Experimental S01  S02  S03  S04  S05  S06 S07  S08  S09  S10  S11 S12

Order Effects Practice Effect Fatigue Effect Contrast Effect order of presenting the treatments affects the dependent variable Practice Effect improvement in performance with repetition Fatigue Effect decrease in performance with repetition Contrast Effect second response is altered due to the influence of the first Counterbalancing is used to correct order effects:

Counterbalancing Complete Counterbalancing Randomized Block Design helps to minimize order effects Complete Counterbalancing Randomized Block Design Matched Pairs Design Latin Squares

Repeated Measures or Within-Subjects Requirements: Each subject participates in all levels of all independent variables   Advantages: uses fewer subjects than the Between-Subjects Design greater statistical power/ lower score variability takes less time minimizes subject effects  Drawbacks: is difficult to control order effects increases demand characteristics  Control Experimental S01  S02  S03  S04  S05  S06

Mixed-Subjects Requirements: Advantages: Drawbacks: must be at least two independent variables Each subject participates in all levels of just one independent variable   Advantages: uses fewer subjects than the Between-Subjects controls for order effects controls for subject effects Drawbacks: is the most difficult to analyze statistically   Control Experimental S01  S02  S03  S04  S05  S06 S07  S08  S09  S10  S11 S12

Controls: Participants Demand Characteristics participants form expectations about the study and behave differently typically "help" the scientists to support their hypothesis deception helps to counter demand characteristics filler items can be used on surveys to disguise the true DV can ask the participants about their perspectives of the study not really seen in non-participant field setting and naturalistic observations Placebo Groups typically used in drug studies simulates drug taking protocol but has sugar pill replacement placebo effect just thinking you are taking medicine can improve your condition can be a very powerful effect Confederates and Deception are used to keep the subjects from knowing the true nature of the experiment

Controls: Experimenter All subjects need to be treated the same and the experiment must maintain consistency from start to finish. Experimenter Bias the experimenter inadvertently influences the outcome of the an experiment may give one group of subjects hints on how to answer a question could treat the control and experimental groups differently can be biased in the way they score subjective evaluations can make mistakes in data recording. "teacher expectancy" can influence performance just knowing about the study can influence the results must assume the bias will happen if not corrected Solutions to the Experimenter Bias blind designs single-blind experimental design double-blind experimental design simultaneous running of participants experimenters should be well-trained and practice consistent behaviors automatic/computerized scoring

Experimental Validity Construct Validity adequacy of the operational definition of variables does it actually reflect the true meaning of the variable? Internal Validity ability to draw conclusions about causal relationships from our data can you make strong inferences about one variable affecting another? External Validity the extent to which the results can be generalized to other populations and other settings

Ethical Principles and Guidelines for the Protection of Human Subjects (Belmont Report) Beneficience maximize benefits and minimize risks Physical harm Loss of confidentiality Justice is there a fairness in giving benefits and accepting risks Respect for Persons allow subjects to make decisions as to whether to participate Deception Debriefing Informed consent

Informed Consent (APA Guidelines) Purpose of Experiment, Expected Duration, and Procedure Right to decline to participate and withdraw once the study has begun Foreseeable consequences of declining or withdrawing from the study Potential risks, discomfort or adverse effects Any prospective research benefits Limits of confidentiality Incentives for participation Whom to contact with questions about research

Data Collection Presentation Choosing Participants Communication Confidentiality

Debriefing Occurs promptly after the data collection is completed Allows participants the opportunity to obtain information about the study Allows the experimenter to explain: any deceptive techniques that were used any risks associated with the study. any misperceptions about the study the purpose of study

Data Entry Should ALWAYS be done with TWO people Go very slow Double Check your work Save your spreadsheet often Create an Excel Spreadsheet Create an SPSS Spreadsheet Save on Data Sticks and Bring to Class Make Back-Up and leave at Home

Data Analysis Graphs Descriptive Statistics Inferential Statistics

Which Statistic Do I Use? Dependent Variable Type Continuous Categorical Number of Factors (Independent Variables) One Two or More (Factorial Analysis) Number of Levels (of the Independent Variable) Two Three or More (Between or Repeated Measures)