Psyc 3000
Download
1 / 92

PSYC 3000 - PowerPoint PPT Presentation


  • 189 Views
  • Uploaded on

PSYC 3000. PSYC 3000. C1-1 Know the five steps involved in the scientific method. “Know” means to be able to list and briefly describe each step (14-18). ID problem: form hypothesis (a stated relationship between 2 or more variables) Design experiment: control for extraneous variables

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'PSYC 3000' - Lucy


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Psyc 30001
PSYC 3000

C1-1 Know the five steps involved in the scientific method. “Know” means to be able to list and briefly describe each step (14-18).

  • ID problem: form hypothesis (a stated relationship between 2 or more variables)

  • Design experiment: control for extraneous variables

  • Conduct experiment

  • Analyze, interpret data

  • Communicate results


Advantage of scientific approach
Advantage of scientific approach…

C1-2. What is the advantage that the scientific method offers over the other five non-scientific methods (19,3-20,0)?

Objective observation: no personal bias/opinion


Characteristics of science
Characteristics of science….

C1-3. List and describe, and give the relevance of each of the characteristics of the scientific approach (control, operational definition, replication). Be prepared to provide an operational definition of some concept that I might give you on the test (e.g., intelligence, anger).

  • Control: eliminating influence of extraneous variables

  • Operational define: terms and variables defined by steps or operations used to measure them

  • Replicate: data must be reliable/replicable

    *Operationally define “Intelligent”


Operations def
Operations Def…

An operational definition of “Stupid” might be

  • Dumb

  • Unable to finish (no longer scrubbing) washing one’s hair within 5 minutes

  • Acts weird in public

  • Burps and acts like a wise-guy when sitting in a classroom

  • Doesn’t think well


Four objectives of science
Four objectives of Science

C1-4.Know the four objectives of science. On an exam, I might give you an example and request that you use the example to illustrate each of the objectives (26-29).

  • Describe: operationalize/define carefully

  • Explain: determine cause

  • Prediction: determine when event will occur

  • Control: produce event by manipulating antecedents (“make behavior happen”)


Five assumptions
Five Assumptions ….

C1-5. Your author identifies five assumptions underlying science, starting with “Determinism”, with each point identified by a subheading. Be able to list and briefly describe each of these points (29-31).

Determinism: causes of behavior and they are accessible (all behavior is caused)

Reality in nature: events/objects in nature are real (vs. Plato: only real through perception)

Rationality: events occur for logical reasons (can use reason to understand)

Regularity: same laws of nature apply everywhere/all the time

Discoverability: it’s possible to discover regularities and causes




Quiz!

Reason is able to be used to help us understand the world, as the world operates in a logical manner. This is an example of:

A. Determinism

B. Reality in nature

C. Rationality

D. Regularity

E. Discoverability


Descriptive research approaches chapter 2
Descriptive Research Approaches…. (chapter 2!)

C2-1. Know the primary characteristic of the descriptive research approach (45,5) and for each of the descriptive research methods I cover in class. Be able to briefly describe what each is, and list the advantages and disadvantages (46-72).

Descriptive Research Approach: observational, non-scientific

  • Accurately describes events/situations

  • No attempt @ discovering cause and effect relations

    Several methods (a sample):

    Secondary records: birth records, census, video recordings, etc.

    ADV: no reactivity

    DisADV:

    Selective Deposit—only some events recorded

    Selective Survival—only some records survive

    Example: Crack babies—reported in 1990s and beyond, but not available pre-1980s

    Naturalistic Study: observe naturally occurring behavior

    ADV: little reactivity; no artificiality

    DisADV: causes not discovered; time-consuming

    Example: Jane Goodall & chimpanzees; Diane Fossi & apes


Descriptive research approaches
Descriptive Research Approaches….

Correlation Study: measure 2 or more variables & determine degree relationship between them.

ADV: able to predict

DisADV: third variable problem

Example: SAT and GPA, Height & Weight

Case Study: observe individual, event, or group

ADV: intense observation of usually rare event

DisADV: little control; can’t generalize; can’t ID causes

Example: Freud’s methods

Longitudinal Study: study individuals or some variable over a relatively long time period

ADV: can see developmental changes over time

DisADV: time consuming; no cause and effect; lose participants

Example: follow set of students from childhood to adulthood (developmental psych.)


Descriptive research approaches1
Descriptive Research Approaches….

Cross-sectional: study different age individuals on some variable. Similar to longitudinal, but don’t follow over time—instead, get different aged participants.

ADV: can examine developmental changes or skills at various age levels; less time-consuming

DisADV: no cause and effect; cohort effect—different age groups may have been exposed to events that changed them (like 9/11 - a confound)

Example: study participants aged 2, 4, 8, & 10 years

Survey: snapshot of current attitudes, beliefs, etc. (“verbal reports”)

ADV: may be predictive; some insight into current events

DisADV: easily biased; people are poor observers of own behavior (inaccurate); positive self-presentation by participants

Example: Gallup polls, Nielsen’s, etc.


Descriptive research approaches2
Descriptive Research Approaches….

C2-2 Know my point to be made in class regarding the survey as a verbal report versus direct observation of behavior. Also be able to recognize examples of and generate original examples of open-ended and close-ended survey questions. Be able to identify “double-barreled” questions as well as knowing the important points listed under the headings “ordering of the questions” and “questionnaire length” (65-66).

Verbal Report is influenced by many things – language is easy to emit – often inaccurate. Comparisons of direct observation vs. verbal self reports reveal self report inaccurate!

But… survey can give some preliminary information so….

  • Ordering of questions: demographic questions first, because they are easy and “lead into” harder ones.

  • Short is better; in person is better (mail return is <2%).

  • Open-ended questions: Answer any way you want to.

  • Close-ended question: Limiting responses; easy to score.

  • Double-barreled: Two questions with only one response…how score??

  • Biased: Slanted; leading to answer in a particular way.


Population sample random sampling
Population, Sample, & Random Sampling

C2-3 Know the difference between the terms “population” and “sample” and know what “haphazard sampling” and “random sampling” are (67).

Population: All people you are interested in

Sample: a subset of the population you are interested in

Haphazard Sampling: nonprobability; obtain participants where you find them. Could be a biased sample.

Random Sampling: every member of population has an equal chance of being selected.


Random sampling
Random Sampling

1 = Random sampling, 2 = Haphazard sampling

You select every other person in the Turlock phone book for your study (your pop is all the folks in Turlock)


Random sampling1
Random Sampling

1 = Random sampling, 2 = Haphazard sampling

You put all the names of everyone in the Turlock phone book into a hat, shake it up, then pull out 20 names that will be in your study.


Random sampling2
Random Sampling

1 = Random sampling, 2 = Haphazard sampling

You put all the names of everyone in this class into a hat, shake it up, the take out 10 names who will be in your study. The class is your population of interest.


The experimental approach
The Experimental approach

C 3-1 What occurs in an experiment?

An experiment involves the independent variable being manipulated and others being controlled (the potential extraneous variables)


Advantages of experimental approach
Advantages of Experimental approach

C 3-2 Know the advantages of the experimental approach—three are listed. Also know the disadvantages (also three listed) (87-89)

Advantages of the experimental approach:

* causal relationships can be stated with confidence

* precisely manipulate one or more variables

* usefulness—leads to solutions/more research

Disadvantages

* poor generalization from lab to “real” life

* experiments are time consuming


Field vs lab
Field vs. Lab

C3-3 Compare and contrast field experimentation and laboratory experimentation. What are the advantages and disadvantages of each? (92-95)

Field Experiment

Experiment conducted in real life setting (need manipulation)

ADV: little artificiality (better generalization)

DisADV: little control over extraneous variables (unsure of results due to IV or EX)

Lab Experiment

ADV: excellent control

DisADV: Artificial (little generalization)




Researchable or not
Researchable or not?

C4-1 Be sure to identify and generate examples of ideas that are and are not researchable (108)

Researchable and non-researchable ideas

  • Researchable: (must be observable /measurable/ testable – empirical)

    b. Non-researchable: typically morality/religion/value judgment issues – non empirical!


A man s soul weighs more than a woman s soul

:45

0 of 35

A man’s soul weighs more than a woman’s soul

  • Researchable

  • Not researchable


The fastest way to modesto is via the back roads santa fe versus 99

:45

0 of 35

The fastest way to Modesto is via the back roads (Santa Fe) versus 99.

  • Researchable

  • Not Researchable


Praying to god will reduce the length of a cold

:45

0 of 35

Praying to God will reduce the length of a cold

  • Researchable

  • Not researchable


How long one can hold a 10 lb weight over their head

:45

0 of 35

How long one can hold a 10 lb weight over their head

  • Not researchable

  • Researchable


Why review the literature
Why review the literature?

C4-2. What are the benefits of reviewing the literature? (109) I found two points.

  • find out what’s been done

    b. point out methodological problems


Criteria for research problem
Criteria for research problem

C4-3. Know the criteria in defining a research problem (“research question” is probably a better way to state this instead of conceptualizing all research as ‘problems’) and be able to generate examples or recognize examples of good and bad research questions (117-120).

Criteria for the selection of a research question

  • states relation between 2 or more variables (often specifies direction of relationship)

    b. should be empirically testable


Scientific vs null hypothesis
Scientific vs. Null hypothesis

C-4-4. Be able to clearly distinguish between a scientific hypothesis and a null hypothesis (120-122). Why is a null hypothesis tested and what is said when it is rejected? (122,0)

Hypothesis: A statement specifying a relationship between 2 or more variables and is testable

Scientific hypothesis: Predicted relationship among variables being investigated.

Null hypothesis: A statement specifying no relationship among variables being investigated.

IV has no effect of DV if null is correct.

Reject the null = IV affected DV significantly


You state that caffeine will improve test scores

:45

0 of 35

You state that caffeine will improve test scores

  • Scientific hypothesis

  • Null Hypothesis


You believe that caffeine will decrease test scores

:45

0 of 35

You believe that caffeine will decrease test scores

  • Scientific hypothesis

  • Null Hypothesis


:45

0 of 35

You state that you drinking watermelon juice prior to taking a test will not result in any change in one’s test scores.

  • Scientific hypothesis

  • Null Hypothesis


All about ethics in research
All about ethics in research

C5-1 Ethics in research

  • Milgram, Syphillis, huh?

  • APA code for ethical treatment

  • Types of stress: Physiological, psychological

  • Exempt vs. nonexempt

  • Informed consent

    • Some aspects: Confidentiality, special populations, right to withdraw, right to results, right to effective treatment,

  • Overriding principle, benefit outweigh cost


Iv and dv
IV and DV

C6-1.Be able to define, recognize examples of and generate examples of variable, IV, DV, discrete variables, continuous variables, qualitative variables, and quantitative variables (191-193).

Variable: measurable characteristic

Independent Variable: Antecedent variable/manipulated

Dependent Variable: Variable measured; detects influence of IV

Qualitative Variable: Vary in kind

Quantitative Variable: Vary in amount


The amount of caffeine in the bloodstream after drinking coffee is

:45

0 of 35

The amount of caffeine in the bloodstream after drinking coffee is ….

  • Independent Variable

  • Dependent Variable

  • Factorial design

  • Anova

  • None of these


How fast one runs a mile after work is an example of

:45

0 of 35

How fast one runs a mile after work is an example of

  • Independent Variable

  • Dependent Variable

  • Factorial design

  • Anova

  • None of these


How fast one hands out a test slow or fast

:45

0 of 35

How fast one hands out a test (slow or fast)

  • Independent Variable

  • Dependent Variable

  • Factorial design

  • Anova

  • None of these

  • Could be either


Iv and dv1
IV and DV

C6-2. Know the two requirements for a variable to qualify as an independent variable (194, 1). Be able to list and describe the three methods the author gives for manipulating variation (1194-197). Note that these categories are not independent of one another (lecture).

IV must:

be variable

be able to be manipulated

Three methods of manipulation:

  • presence/absence

  • amount of variable

  • type of variable


Iv and dv2
IV and DV

C6-3. Be prepared to recognize and generate examples of operationally defined IVs (205-207).

Be able to give examples.

Give an operational definition of an IV and a DV.

E.g. provide an example of manipulating self esteem as and IV, or measuring self esteem as a DV.


Construct validity
Construct Validity

C6-4. Know the definition of "Construct Validity” and how it is established (2 methods listed in 209, 2-3). Also know the three methods for checking on the manipulation of the IV (210, 3-211,3).

Construct: a consistent set of behaviors with a label on it, i.e., friendly, athletic, etc.

Construct Validity of the IV (operationally defined): The extent to which an abstract construct can be inferred from the operational definition of that construct.

Establish by…

  • Clear operational definition of abstract construct

  • Showing convergent (expected outcomes) and divergent data (diff measure and no relation to outcomes)


Manipulating the iv
Manipulating the IV

C6-4. Know the definition of "Construct Validity” and how it is established (2 methods listed in 209, 2-3). Also know the three methods for checking on the manipulation of the IV (210, 3-211,3).

Checking on manipulation of IV:

Interview participants: to ensure that the IV had the desired effect on them.

Behavioral Indicator (blood pressure/EEG/GSR) (or physiological indicators)

Pretesting/pilot data


More than one iv
More than one IV

C6-4. What is the advantage of using more than one IV? Be able to define “Interaction” and give examples of it (212).

Number of IVs:

More than 1 gives interaction data (in addition to main effects) = Different effect a variable has on different levels of other variables

Test

scores

Vitamins No vitamins

Interaction Graph

Make experiment only as complex as needed to show relationships clearly!

factorial design (2X2; 2X4; etc.)

Exercise

No Exercise




DV

C6-6.Know the definition of “DV”(213,1). What are the tasks of a DV (214,2-215,1). Your author lists three aspects of an experiment related to the DV that must be considered by the researcher. These include selecting the DV, the subject’s motivation level (“taking it seriously” p 215,1) and “cooperating” (215,1).

DV: The behavioral variable designed to measure the effect of the variation of the independent variable.

Dependent variable: should be:

  • Sensitive

  • Must ensure participant being serious and not “cooperative”


Reliability and validity
Reliability and Validity

C6-7. Know the difference between and the definition of reliability and validity. How are each established (217-221).

Reliability of DV:

Extent to which the dependent variable is consistent or stable over time. Measure must be reliable over time.

Do replications and see if get similar measures on the DV

Validity: The extent to which the DV measures what you want to measure

Check by:

Convergent data: extent to which similar measures correspond to measure used

Divergent data: extent to which dissimilar measures do not correspond to measures used


Disguising the dv
Disguising the DV

C6-8. What are the benefits of disguising the DV (221,2)? (through distractions)

  • Participants take measure seriously

  • Participants’ demand characteristics controlled for


Internal validity
Internal Validity

C7-1. Know the definitions of internal validity and extraneous variable (229). What are the two methods of controlling extraneous variables (230-232). Know the point made in 232,2 regarding “The difficulty frequency lies in identifying those variables.”

Internal Validity:

Extent to which one can accurately state that the IV produced any observed effects on DV.

Extraneous variables controlled by:

  • Elimination

  • Keep constant across groups/eliminate difference between groups (random assignment)

    You can’t identify all “participant variables” (possibly confounds such as gender, age, IQ, experience, etc.) . Can only control through random assignment (by balancing experimental and control groups)


Extraneous variables
Extraneous variables

C7-2. Be able to list and define the six extraneous variables that Christensen notes need to be controlled for. Be able to give an example of each and to recognize examples of each (233-240). (Most relate to pre-post-test design)

History—something which occurs between a pre & post test and may effect DV

Maturation—biological/psychological changes that occur with time passage

Instrumentation—assessment tool/person changes during course of study. Change in DV may be due to this. (combat with interobserver agreement)

StatisticalRegression—high and low scores in a distribution will tend to regress back toward the mean (change in DV may be due to this) (usually happens with tests to raise very low scores) prevent: don’t use highs and lows, use a range. detect: use control group which should mimic stat. reg. (byproduct of poor selection)

Selection—when the selection of participants is NQR (not quite right) and the various groups are unequal in composition. Thus characteristics of participants may cause observed effect.

Mortality—unequal loss of participants from the various groups in the experiment (may account for difference between groups).


45

0 of 35

Your research assistants start to like your research participant in a study designed to help folks to stop smoking. They gradually change their criteria to what is considered smoking from simply putting the cigarette in one’s mouth to actually breathing in smoke. This makes it look like the DV had decreases when it has not. This is called:

  • Statistical regression

  • Mortality problem

  • Maturation problem

  • History problem

  • Selection problem

  • Instrumentation problem


0

0 of 35

You are measuring the effects of caffeine on people who experience panic attacks. One of your caffeine groups is “run” over the fourth of July weekend. This could be an example of….

  • Statistical regression

  • Mortality problem

  • Maturation problem

  • History problem

  • Selection problem

  • Instrumentation problem


Participant effects
Participant Effects

C7-3a. Be able to list and define the participant effects (demand characteristics, positive self-presentation) the experimenter effects (experimenter attributes, experimenter expectancies). In the section labeled experimenter expectancies, know the different effects on the experimenter and the participants (240-255)

Participant effects

A. Demand characteristics: cues which give participant clues as to the nature of the experiment and they change their behavior.

B. Positive self-presentation: participants try to appear positive (and often use demand chars. in this quest!)


Kjfkjsdkfjksdjf

:00

21 of 35

kjfkjsdkfjksdjf

  • Appropriate

  • Inappropriate


Experimenter effects
Experimenter Effects

C7-3b. Be able to list and define the participant effects (demand characteristics, positive self-presentation) the experimenter effects (experimenter attributes, experimenter expectancies). In the section labeled experimenter expectancies, know the different effects on the experimenter and the participants (240-255)

  • Experimenter effects:

    Attributes: the characteristics or skills of experimenter may influence results. (gender, method of delivery, etc.)

    Experimenter Expectancies: influence of the experimenter’s expectancies on outcomes.

    • Recording Bias

    • In interpreting data

    • Affect participants’ responses


More extraneous vars
More Extraneous vars

C7-4. Know what a sequencing effect is, as well as subject sophistication (255-257).

More extraneous variables:

  • Sequencing effect: prior treatment affects subsequent conditions

  • Participant sophistication: being familiar with subject matter or with materials/procedure (more of a problem with repeated measures designs)


Randomization
Randomization

C8-1. Know what Randomization is, what it accomplishes (mention 'unknown sources of variation')(264), and how to do it (exhibit 8.1, page 266). What does "representative" mean? (267).

Randomization: The only known technique for controlling unknown sources of variation; every member of a population has an equal chance of being selected. (participant variables/extraneous variables)

Representative (Random selection): The extent to which a sample is similar in composition to a population.

Random Assignment should: Distribute potential extraneous variables equally to various groups.

--by chance may get bias

--the larger the sample, the less likely bias will occur


Random selection and assignment
Random Selection and Assignment

C8-2. What does Random Selection (sampling) assure, and what does Random Assignment Assure? (267,0)

Random Sampling (selection) assures a representative sample

Random Assignment assures a equal distribution of extraneous variables (participant variables) thus making your control and experiment groups equal in those potential confounding variables.


More extraneous vars1
More Extraneous vars

C8-3. Be able to define matching and know the two benefits (273-274,0)

Matching: equating groups on one or more variables by measuring participants on those variables and assigning them in equal amounts to the various groups.

ADV.

increases sensitivity of experiment (the DV)

More balanced groups

DisADV: time-consuming; pre-measuring induces demand characteristics

Precision Matching: each participant is matched to another on some variable.

Example

Step 1: Measure on variable suspected of having impact

Step 2: put in order

Step 3: Block according to number of groups

Step 4: RA participants from a block to one group – repeat this for each block.


Matching
Matching

C8-4. Be able to define matching and know the two benefits (273-274,0)

Three groups – IV = Rock music, Classical music, no music

DV = performance on a math test

Matching Variable: IQ scores

112

101

132

117

104

124

136

118

99

113

140

106


Controlling subject effects
Controlling Subject Effects

C8-5. Know and be able to briefly describe the five general methods for controlling subjects effects (Double-blind placebo, deception, disguised experiment, independent measure of the dependent variable, and procedural/control of subject interpretation)(291-297)

Four General Methods for Controlling Subject Effects

1) Double-Blind Placebo: Experimenter and participant unaware of the conditions in effect (but aware they are in an experiment).

2) Deception: Misdirect participants as to the nature of the experiment.

3) Disguised Experiment: Participant is not aware they are participating in an experiment.

4) Independent Measures of the DV: Measure the DV away from the experimental condition.

5) Procedural control/control of participant interpretation – gain insight into participants perceptions:

A. Retrospective verbal report (exit interview)

B. Concurrent Verbal Reports (think aloud)

C. Sacrifice groups (terminate at various times)


Control recording errors
Control Recording Errors

C8-6. Know the various methods for control of recording errors:

Maintain observer awareness—continuous training

Multiple observers—inter-observer agreements

“Blind” data recorders—unaware of conditions in effect

Automation—computer/videos, etc.


Control recording errors1
Control Recording Errors

C8-7. Be able to list, describe, or to apply any of the three "Control of Experimenter Expectancy Errors

  • Blind Technique – experimenter unaware of conditions (reduces bias)

  • Partial blind technique – keep experimenter “blind” as long as possible (reduces bias)

  • Automation – use computer, video tapes, audio recordings – minimizes errors


0

20 of 35

A micro-switch in the base of little Johnny's chair allows us to detect if he gets off his seat. The experiment is investigating if caffeine increases these out of seat episodes. The teacher is unaware if Johnny had caffeine or placebo. This is an example of…

  • Automation

  • Blind technique

  • Multiple observers

  • Number 1 & 2

  • Nada!


Faulty designs
Faulty Designs

C9-1. Given a scenario which describes any of the faulty research designs, you should be able to point out the faults (e.g. potential confounds). There are three type of faulty experiments described (313-317)

A.  1-group after-only design: one group is measured on the DV after IV is manipulated/administered did a change in performance occur? For what reasons?

B.      1-group before-after design (pretest/posttest): change could be due to history/maturation/instrumentation/stat regression

C. Non-equivalent posttest only: could be differences between groups causing effects (ex. Joiners vs. nonjoiners) too small of a sample or not randomly assigned


True research design
True Research Design

C9-2. Be able to list and describe the three criterion that a true research design must meet:

A. Adequate answering of question/test of hypothesis (317,1)

B. Control of extraneous variables (318,1)

C. Allows for generalizability/external validity (319,3)


True research design1
True Research Design

C9-3. Know what a control and experimental group is, and the two functions that a control group serves (318,4-319,1)

Experimental group—receives some level of the IV

Control group receives no IV or some fixed/traditional level

Control group allows:

1.         Comparison of scores with experimental group

2.       “Control for rival hypotheses” meaning detect extraneous variable influences. (detect by looking at the changes…if DV changes also, then confound)


True research design2
True Research Design

C9-4. Be able to list and briefly describe the five reasons a pretest might be incorporated into a study. (320-322). Also know the two disadvantages of the pretest (322,3)

 Pretest might be incorporated for:

1)        increased sensitivity/matching

2)      to determine if ceiling/ floor effect

3)      get initial position/attitudes

4)      similar initial comparability: compare subjects

5)      evidence of change (after posttest)

Disadvantages

Expensive

Demand characteristics


After only designs
After Only Designs

C9-5. There are six "After-Only Designs" described in your text (323-341). Be able to describe each and list the advantages and disadvantages. Do the same for the Before-After Design described in 339-341.

1 Between groups/participants after-only design

(diff. parts. in each group)

a.        Control and experimental group

b.       Random selection and random assignment

Disadvantage:

Randomization could be biased (likelihood is a function of sample size)

Not matched = less sensitive design


After only designs1
After Only Designs

   Simple Randomized Participants Design

A.         Control and experimental group

B. Random selection and random assignment

C. More than one level of the IV


After only designs2
After Only Designs

Factorial Design

a.        Control and experimental group

b.       Random selection and random assignment

c.        More than one level of the IV and more than one IV

 Can determine:

Main effect: the effect of each IV taken alone

Interaction effect: the effects one may have on DIFFERENT levels of another IV

Know:

2 x 2

2 x 3 x 2

2 x 4 x 6 x 2 (levels, # of variables, total number of participants)


A 2x2x5 factorial design has

:40

0 of 35

A 2x2x5 factorial design has

  • 1 IV

  • 20 Ivs

  • 3 Ivs

  • 9 IVs


A 3 x 6 factorial design has

:40

0 of 35

A 3 x 6 factorial design has

  • 18 groups

  • 9 groups

  • 2 groups

  • 36 groups


A 2 x 2 design could be

:40

0 of 35

A 2 X 2 design could be

  • 0, 1, and 2 mg of caffeine and gender

  • Gender and room color: red, blue, green orange and white

  • Gender and a hot room or a cold room

  • Caffeine or not, and room color: blue, red, green.


A 2 x 2 design with 20 people per group has

:40

0 of 35

A 2 x 2 design, with 20 people per group, has

  • 24 participants

  • 80 participants

  • 40 participants

  • 100 participants

  • 20 participants


After only designs3
After Only Designs

C9-6. In regard to a factorial design (328-335), know what a cell refers to; what the main effect and interaction effects are; and be able to recognize graphical displays of interaction effects (e.g. if they exist or not see figure 9.10)

Interpreting factorial design results

1)  If only main or only interaction effects, interpret both

2) If main and interaction effects: interpret only interaction effects

Problems with factorial:

1)        More factors = lots more participants

2)      Hard to manipulate more than 2 IVs

3)      Triple interactions and more = hard to interpret

Advantages of Factorial

1)        Test more (more IVs)

2)      Can build extraneous variables into experiment (like gender…crowding…aggression levels)

Can examine interactions (also more like real world)


After only designs4
After Only Designs

4) Within-groups/participants after-only design (repeated measures)

all participants get all treatments

Advantages:

don’t have to create equivalence on participant variables

fewer participants

Disadvantages:

sequencing effects (who goes first/second) control with counterbalancing

no control (detection) of history/maturation, etc.


After only designs5
After Only Designs

Combining Between and Within Subject Designs

(a factorial design)

More Variables studied

Less subjects than a pure between design

Can test for interactions IV 1

IV 2


Single subject designs
Single Subject Designs

C11-1. Know what a single-SUBJECT design is in general (be able to describe its components) (373-377). Add to this that seldom is a single participant only used—usually 5-6 is used, providing replication evidence for any observed effects (lecture).

Examine one participant at a time to investigate the effects of an IV (treatment).

  • Repeated measures

  • “Baseline as a control and comparison”

  • Use multiple participants = replications


Single subject designs1
Single Subject Designs

C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).

ABA design

Baseline (A) – Treatment (B) – Baseline (A)

Withdrawal lends evidence that treatment caused effect!

 ABAB design

More evidence!

Interaction Designs: Interaction refers to having two IVs present at the same time thus:

A B A B A BC A B A……..


Single subject designs2
Single Subject Designs

Baseline - A

Treatment - B

Baseline - A

DV

Be able to create an ABA, or ABAB graph


Single subject designs3
Single Subject Designs

C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).

Multiple Baseline designs (across participants or situations/locations)

Baseline is recorded during the same time period for different lengths of time, for multiple participants. The treatment (IV) is introduced at different times for each participant (baseline is staggered/switch to IV is at different times for each participant to gauge the effect of IV)

No change in ongoing baseline is evidence that extraneous variables are NOT at work


Single subject designs4
Single Subject Designs

C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).

Multiple Baseline designs

From: http://curry.edschool.virginia.edu/class/edlf/733/acts/mbline.html


Single subject designs5
Single Subject Designs

Changing criterion designs

  • If effects follow the change in the criterion (the IV) then evidence supports the IV causes effect in the DV.


Single subject designs6
Single Subject Designs

Changing criterion designs

From:http://www.radford.edu/~pjackson/2SmallN.pdf


Single subject designs7
Single Subject Designs

  • Know the methodological considerations in using single-participant designs. Under the heading “Baseline,” I found four points regarding a stable baseline (absence of a trend; trend opposite to treatment effect; excessive variability; and reactivity). Know the critical issues related to changing one variable at a time (only change one!) (395,3-398).

  • Stable baseline is characterized by:

    • Absence of trend and only slight degree of variability (e.g. w/in 5% mean)

    • Trend opposite, treatment is powerful enough to produce effect and reverse previous

    • Extreme fluctuations: check all components of the study and try to identify and control sources of variability

    • Reactivity: fact of using human participants—taking data itself may effect behavior


Single subject designs8
Single Subject Designs

Knowing when to change from baseline to intervention:

1) Shouldn’t change baseline until observe:

Little variability

No trends

(but could if trend is opposite in direction to expected effect)

2) Only change one variable at time!

(Examples on board)


Single subject designs9
Single Subject Designs

Knowing when to change from baseline to intervention:

1) Shouldn’t change baseline until observe:

Little variability

No trends

(but could if trend is opposite in direction to expected effect)

2) Only change one variable at time!

(Examples on board)


Scales of measurement
Scales of Measurement

S1-1. Scales of Measurement: important for selecting stat's (later on)

1. Nominal Scale: number is really a name!

1 = male 2 = female

2. Ordinal Scale: number represents degree of an attribute: (order things!)

take all exams and rank: 1,2,3,4,5,

but 5-1 = 4 no information!

3. Interval Scale:

A. different degrees of an attribute are indicated

B. different levels, or degree numbers are equally spaced

C. zero point is arbitrary (doesn't indicate absence of variable)

4. Ratio Scale:

A. numbers are equidistant (as in interval)

B. numbers indicate diff. degree of attribute

C. O indicates absence of attribute


Which one is nominal

45

0 of 5

Which one is nominal?

  • The number of cigarettes a person smokes in a day

  • Level in school: freshman= 1, sophomore=2, etc.

  • Age in years

    4. How happy are you?

    none 0 ------5 --------10 Lots


Which one is ratio

45

0 of 5

Which one is ratio?

  • Blood pressure level

  • Heart beat rate

  • Age in years

  • Number of dates one had last week

  • The number of hours of TV watched in a month

  • All of the above

  • None of the above

  • I haven’t the faintest!


ad