final

Question 1

Experiment

Answer 1

Operationally define variables
Attempts to establish cause and effect relationships
Causal variable = Independent Variable
Effect variable = Dependent Variable
Researcher manipulates IV so that different levels of variable are applied (and later results of levels are compared)
Participants randomly assigned to groups, each receives “one level” of the IV

Question 2

Strength

Answer 2

Identification of causal relationships among variables

Not possible with correlational research

Question 3

Limitations

Answer 3

Can’t use experimental method if you cannot manipulate variables and randomly assign participants to experimental groups

What is Manipulation?

What is Random assignment?

Tight control over extraneous variables limits generality of results
Tradeoff exists between tight control and generality

Question 4

Control

Answer 4

efforts by the researcher to remove the influence of any variable, with the exception of the Independent Variables (IVs), on the Dependent Variables (DVs)

Question 5

Three Types of Variance in an Experiment

Answer 5

Experimental variance 
desirable, seek to maximize effect of IV on DV
Variance from Extraneous Variables 
undesirable, seek to minimize
Error Variance 
undesirable, seek to minimize
Sampling error
Measurement error

Question 6

Experimental Variance

Answer 6

Desire to find difference between groups on DV measure
Different levels of IV&raquo_space;> different levels of effect on DV
Ex: Effects of caffeine on task performance
Define variables
Levels of IV?
DVs to measure task performance

Question 7

Control Extraneous Variables

Answer 7

Extraneous variable = any variable that could have unintended effect on DV
Confounding = results of experiment may be due to either IV or extraneous V
Control by
Randomization – random selection & assignment
Hold constant – homogeneous grouping
Use as IV
Matched pairs
Counterbalancing – control order effects by presenting different treatment sequences

Question 8

Extraneous variable

Answer 8

any variable that could have unintended effect on DV

Question 9

Confounding

Answer 9

results of experiment may be due to either IV or extraneous V

Question 10

Counterbalancing

Answer 10

Sequence or Order Effects:
Sequence or order effects are produced by the participants being exposed to the sequential presentation of the treatments.

Carryover Effects:
The effects of one treatment persist or carry over and influence responses to the next treatment.

Question 11

Power

Answer 11

the probability that a statistical test will be significant (i.e., the experimental hypothesis is accepted when it is true).

The number of participants tested is related to the power of our statistical test.

Question 12

Homogeneity/Heterogeneity

Answer 12

may influence number of participants needed in your experiment.

Lower within-group variability (i.e., the more homogeneous the participants), the fewer participants needed

Higher within-group variability (i.e., the more heterogeneous the participants), more participants needed.

Maximize N and n !!

Question 13

Could You influence/interfere with your own experiment?

Experimenter Characteristics

Answer 13

Physiological
Characteristics such as age, sex, and race may have an influence on participants’ responses

Psychological
Characteristics such as hostility, anxiety, introversion or extraversion also influence on participants’ responses

Question 14

Control Experimenter Characteristics

Answer 14

Constancy in Experimenter - gender, appearance, age, manner, treatment of participants

Question 15

Experimenter Expectancies

Answer 15

influence of the Experimenter’s expectations on outcome of study

expectations that cause him/her to behave toward participants in such a manner that elicits the expected response

Rosenthal effect

Question 16

Rosenthal effect

Answer 16

= Experimenter’s preconceived idea of appropriate responding influences the treatment of participants and their behavior.

Question 17

Control Experimenter Expectancies

Answer 17

Script for instructions, procedure should be standard for all groups
Standard method of recording responses
Single-blind experiment – experimenter unaware of IV level

Question 18

Participant Perceptions as Extraneous Variables

Demand characteristics

Answer 18

= features of the experiment that inadvertently lead participants to respond in a particular manner

Psychology is interesting and Participants are smart!
may attempt to figure out experiment and how they are “should” respond and then behave in that manner

Control by
using double-blind experiment = both experimenter and participants are unaware of which treatment condition
mask true nature of experiment

Question 19

Participant Perceptions as Extraneous Variables

Good participant effect =

Answer 19

tendency of participants to behave as they perceive the experimenter wants them to

Question 20

Participant Perceptions as Extraneous Variables

Response bias

Answer 20

Tendency to agree (disagree), respond as cued by Context: Environment, Experimenter manner, questionnaire context

Question 21

Controlling Participant Effects

Answer 21

Yea-saying & Nay-saying
Have some items for which a negative response represents agreement (control for yea-saying) or a positive response represents disagreement (control for nay-saying)

Run pilot study
Test your procedure on a few people before true data collection

Question 22

Internal Validity

Answer 22

the extent to which your IV caused changes your DV.

Given adequate control techniques, your experiment should be free from confounding, therefore high in internal validity

Question 23

Internal Validity: History

Answer 23

History refers to significant events that occur between the DV measurements in a repeated measures design.
Pre-test . . . Post-test (only treatment should effect; drug tx = IV, some participants exercise)
DV measured over time (DV anxiety changing due IV events, loud noise occurs)

Question 24

Internal Validity: Maturation

Answer 24

refers to changes in participants that occur over time during an experiment.
These changes could include actual physical maturation or tiredness, boredom, hunger, and so on.

Question 25

Internal Validity: Testing

Answer 25

When measuring the DV causes a change in the DV practice effect - if you take the same test more than once, scores on the second test may vary systematically from the first scores simply because you took the test a second time.

Question 26

Internal Validity: Reactive Measures

Answer 26

Content or context of measurements actually change the DV being measured. Many attitude questionnaires are reactive measures. Questions measure how you feel about people of different racial groups, or about women’s rights, or about the President’s job performance, you can probably figure out that your attitude is being measured. devise nonreactive measures

Question 27

practice effect

Answer 27

- if you take the same test more than once, scores on the second test may vary systematically from the first scores simply because you took the test a second time.

Question 28

Threats to Internal Validity

Answer 28

Instrumentation (Instrument Decay) Equipment or human measuring the DV changes the measuring criterion over time Statistical Regression Statistical regression occurs when low scorers improve or high scorers fall on a second administration of a test due solely to statistical reasons Selection If we choose participants in such a way that our groups are not equal before the experiment, we cannot be certain that our IV caused any difference we observe after the experiment Ex: All friends in Experimental group Mortality Participants from different groups drop out of the experiment at different rates.

Question 29

External Validity:

Answer 29

extent to which results of an experiment may be generalized to the population behavior

Question 30

Threats to external validity

Answer 30

Interaction of Testing and Treatment pretest sensitizes participants to the upcoming treatment Participants’ reactions to the treatment will be different Control? Interaction of Selection and Treatment when a treatment effect is found only for a specific sample of participants Control? Reactive Arrangements caused by an experimental situation that alters participants’ behavior, regardless of the IV involved Control?

Question 31

Threats to External Validity Cont.

Answer 31

Demand characteristics Features from the experiment that inadvertently lead participants to respond in a particular manner. Control? Convenience Sampling A researcher’s sampling of participants based on ease of locating the participants; often does not involve true random selection. Control?

Question 32

External Validity: Replication

Answer 32

An additional scientific study that is conducted in exactly the same manner as the original research project. When we replicate an experimental finding, we are able to place more confidence in that result. Replication with extension An experiment that seeks to confirm (replicate) a previous finding but does so in a different setting or with different participants or under different conditions.

Question 33

Experimental design

Answer 33

The general plan for selecting participants, assigning participants to experimental conditions, controlling extraneous variables, and gathering data.

Question 34

Principle of parsimony (Occam’s razor)

Answer 34

The belief that explanations of phenomena and events should remain simple until the simple explanations are no longer valid. Facilitated communication believed to provide stability, … complicated explanations when fc could be simply explained by the facilitator physically directing the movements of the autistic person’s arm and hand However, it’s important not to oversimplify research design Must include enough plausible variables to see if/how they are related to each other; ex: faith and health

Question 35

Experiment

Answer 35

Operationally define variables Attempts to establish cause and effect relationships Causal variable = Independent Variable Effect variable = Dependent Variable Researcher manipulates IV so that different levels of the variable are applied Participants randomly assigned to groups, each receives “one level” of the IV

Question 36

Simple Two-group Design:Between-Groups design

Answer 36

Each level of the Independent Variable tested using Different Groups of Participants Experimental group the group of participants that receives the IV Control group the group of participants that does not receive the IV Assigning Participants to Groups Random Assignment A method of assigning research participants to groups so that each participants to groups so that each participant has an equal chance of being in any group. Random assignment is not the same as random selection. When we randomly assign participants to groups, we have created what are known as independent groups. When we wish to compare the performance of participants in these two groups, we are making what is known as a

Question 37

Within Groups Design: Repeated Measures Within-Group comparison . . .

Answer 37

Usually refers to comparisons of repeated measures of DVs We are essentially comparing scores within the same participants (Same Group=Within-Group) Ex: measuring Anxiety across phases of an experiment Before stress induction After stress induction (before difficult task) During difficult cognitive task

Question 38

Comparing Two-Group Designs

Answer 38

Choosing a two-group design Random assignment should equate your groups adequately (assuming that you have large groups). If you are using 20 or more participants per group, you can feel fairly safe that randomization will create equal groups. If you are using 5 or fewer participants in a group, randomization may not work.

Question 39

Error variability = Within-Group variability

Answer 39

Variability in DV scores that is due to factors other than the IV – individual differences, measurement error, and extraneous variation (also known as within-groups variability).

Question 40

Comparing Two-Group Designs: Independent-Groups vs Within-Groups Designs

Answer 40

Independent-groups design Also known as Between-Groups or Between-Subjects design Two groups of (different) Groups Ex: randomized, post-test, control group design First random assignment to two groups, and then Group A Treatment Post-test (Exp’tal gp) Compare by Stat Analysis Group B No Treatment Post-test (Control gp) Also randomized, pretest-posttest design and multiple level, randomized, pretest-posttest design

Question 41

Comparing Two-Group Designs: Independent-Groups vs Within- Groups Designs Within-Groups Designs (Within-Subjects Design)

Answer 41

One group of Groups exposed to all treatment levels Disadvantages of practice, carryover effects, habituating, becoming tired or unmotivated Requires counterbalancing; ex: ½ Groups receive Condition 1 first, other ½ Groups receive Condition 2 first . . . Advantages increases sensitivity to IV by reducing individual difference component of error variance, insures equivalence of groups, fewer Groups needed

Question 42

Statistics

Answer 42

Statistics is a branch of mathematics that involves the collection, analysis, and interpretation of data Two main branches of statistics assist your decisions in different ways Descriptive Statistics Procedures used to summarize a set of data Good to describe your sample Inferential Statistics Inferential statistics are used to analyze data after conducting an experiment to determine whether your independent variable had significant effects on DVs

Question 43

Descriptive Stats

Answer 43

Use to summarize a set or distribution of numbers in order to communicate their essential characteristics One essential characteristic is a measure of the typical or representative score, called a measure of central tendency. A second essential characteristic to know about a distribution is how much variability or spread exists in the scores.

Question 44

Scale of measurement

Answer 44

A set of measurement rules

Question 45

Nominal Scale

Answer 45

A scale of measurement in which events are assigned to categories.

Question 46

Ordinal Scale

Answer 46

A scale of measurement that permits events to be rank ordered.

Question 47

Interval Scale

Answer 47

A scale of measurement that permits rank ordering of events with the assumption of equal intervals between adjacent events.

Question 48

Ratio Scale

Answer 48

A scale of measurement that permits rank ordering of events with the assumption of equal intervals between adjacent events and a true zero point.

Question 49

Histogram

Answer 49

A graph in which the frequency for each category of a quantitative variable is represented as a vertical column that touches the adjacent column.

Question 50

The Relation Between Experimental Design and Statistics

Answer 50

Selecting the appropriate experimental design determines the particular statistical test you will use to analyze your data. You should determine your experimental design Before you begin collecting data to ensure there will be an appropriate statistical test you can use to analyze your data.

Question 51

Analyzing Data from Experiments with One Independent Variable

Answer 51

Statistical analyses depend on the type of dependent variable used To test the diff between groups with nominal data: Chi Square Interval and ratio data: t-test or ANOVA

Question 52

t-test

Answer 52

used to compare two groups at a time

Question 53

Analysis of Variance (ANOVA)

Answer 53

can handle any number of groups (levels of IV) And multiple IVs >>> Factorial ANOVA, ex: 2x2 And multiple DVs >>> MANOVA – multivariate analysis of variance

Question 54

ANOVA: Analysis of Variance Within-Groups Variance

Answer 54

involves analyzing variance in two ways: 1) within-groups variance and 2) between-groups variance Within-Groups Variance = nonsystematic variation in the group Represents chance variation among participants + error (individual differences & measurement error) = average variability within each group

Question 55

ANOVA: Analysis of Variance

Answer 55

Between-Groups Variance = measure of systematic variation and variation due to sampling error & experimental error systematic factors = 1) experimental variance (due to IV) 2) extraneous variance (due to confounding variables) F = Between-Groups Variance/ Within-Groups Variance

Question 56

Experiments are arranged to maximize experimental variance, control extraneous variance, and minimize error variance

Answer 56

Variance is based on the sum of squares (SS), which is the sum of the squared deviations from the mean There is a SS on which BG variance is based, and SS on which WG variance is based & a total SS Total SS = Between-Groups SS + Within-Groups SS

Question 57

Steps in Calculating One-way ANOVA

Answer 57

1. Compute sum of squares between groups, within groups, and total sum of squares 2. Compute between groups and within-groups variances (mean squares) by dividing each sum of squares by the appropriate number of df BG SS/5 (Number of groups - 1) WG SS/42 (Number of subjects - number of groups, 48-6=42) 3. Divide between-group mean square by within-group mean square = F ratio

Question 58

ANOVA: Analysis of Variance

Answer 58

Increase BG mean square by maximizing the difference between groups (IV levels distinctively diff to have differential impact) 400 mg vs 0 mg caffeine Minimize WG mean square by controlling as many potential sources of error as possible *** What if the BG variability is same as WG variability?*** That means that the differences between groups are due solely to chance factors & experimental manipulation had no effect BG variability must be significantly larger than WG variability to conclude that the experimental manipulations had effects beyond chance the larger the F-ratio, the greater the difference between groups that was caused by experimental manipulations

Question 59

ANOVA: Analysis of Variance??

Answer 59

One-way ANOVA Summary Table for Aggression and Room Temperature Sum of Mean F p Source d.f. Squares Squares Ratio Prob. Between-Gps 5 1134.67 226.93 5.50 .0006 Within-Gps 42 1731.25 41.22 Total 47 2865.92   If the p-value is less than the alpha level (.05, .01, .001) chosen, reject the null hypothesis and conclude that at least one of the groups is significantly different from at least one other group

Question 60

Measures of Association

Answer 60

Used when you want to determine the direction and degree of relationship between variables Various measures of association available for different applications

Question 61

The Pearson Product–Moment Correlation (r)

Answer 61

Most widely used measure of association Value of r can range from +1 to 0 to –1 Magnitude or strength of r tells you the degree of LINEAR relationship between variables Sign of r tells you the direction (positive or negative) of the relationship between variables

Question 62

The Pearson Product–Moment Correlation (r)

Answer 62

Presence of outliers affects the sign and magnitude of r Variability of scores within a distribution affects the value of r Used when scores are normally distributed

Question 63

Measures of Association: Pearson Product-Moment Correlation

Answer 63

Index of linear relationship between two continuously measured variables

Question 64

Measures of Association: Point-Biserial Correlation

Answer 64

Index of correlation between two variables, one of which is measured on a nominal scale and the other on at least an interval scale

Question 65

Measures of Association: Spearman Rank-Order Correlation (rho)

Answer 65

Index of correlation between two variables measured along an ordinal scale

Question 66

Multiple Regression: brief consideration –

Answer 66

The regression weight (b) is based on raw scores and is difficult to interpret The standardized regression weight (beta weight) is based on standard scores and is easier to interpret You can predict a value of Y from a value of X once the regression equation has been calculated The difference between predicted and observed values of Y is the standard error of estimate