Chapter 10: Introduction to Simple Experiments Flashcards
Experiment
- Specifically means that the researchers manipulated at least one variable and measured another
- It can take place in a laboratory and just about anywhere else - anywhere a researcher can manipulate one variable and measure another
Manipulated Variable
A variable that is controlled, such as when the researchers assign participants to a particular level (value) of the variable
- Independent variable
Measured Variable
- Take the from of records of behavior or attitudes, such as self - reports, behavioral observations, or psychological measures
- The researchers simply record what happens
- Dependent variable
Conditions
Levels of an indepedent variable (and it should not be confused with it’s levels)
Control Variable
- Any variable that an experimenter holds constant
- Want to make sure all participants are identical except the variable that is being manipulated
- Also called the nuisance variable
Comparison Group
(comparison condition)
- If the independent varibales did not vary, a study should not establish covariance
Treatment Group(s)
(one or more treatment conditions)
- Give variables on each side such as doeses of medication
Control Group
(no treatment condition)
- It is a level of an independnt variable that is intended to represent “no treatment” or a neutral condition
Placebo Group
(placebo control group; appears to the participants to be an active treatment, but does not actually contain the active treatment)
- When the control group is exposed to a treatment such as sugar
Experiments Establish Temporal Precedence
- Where the cause variable precedes the effect variable
- The ability to establish temporal precedence, by controlling which variables come first, is a strong advantage of experimental designs
- The ability to establish temporal precedence is a feature that makes experiments superior to correlational designs
Confound
- Or potential threats to internal validity
- Can mean confuse
- When a study has a confound, you are confused about what is causing the change in the dependent variable
Design Confound
- Is an experimenters mistake in designing the independent variable
- Is a classic threat to internal validity
- When a experiment has a design confound, it has poor internal validity and cannot support a causal claim
Systematic Varibality
- Don’t want another variable making a change
- It’s a problem
- It is important to reduce systematic variability through proper experimental design and control
Unsystematic Variability
- Less of a problem
- Change that is not consistent
- It is somewhat random
Selection Effect
- When participants in one level is systematic different than the other participants conditions
- When the experimenters let participants choosle (select) which group they want to be in
- May result if the experimenters assign one type of person to one condition, and another type of person to another condition
Random Assignment
- Avoids selection effect
- Random assignment is where every participants have an equal chance of any conditions
- Well-designed experiments often use random assignment to avoid selection effects
- Is a way of systematizing the types of participants who end up in each level of the independent variable
Independent Group Design
(aka between sibjects design or between groups design)
- When participanst are exposed to just one level of condition
Matched Groups
- Avoiding selection effects
- Has the advantage of randomness
- Requires more time and often more resources than random assignment
Within Group Design
(aka within - subjects design)
- Each particpansts are exposed to all levels of conditions
Posttest - Only Design
- Participants are randomly assigned to each level and are tested on the dependent variable once
- Also known as as an equivalent groups
Within - Groups Designs
Participants are exposed to all conditions (levels)
Repeated - Measures Design
Is a type of within - groups design in which participants are measured on a dependent variable more than once, after exposure to each level of the independent variable
Concurrent - Measures Design
Which is when all conditions are exposed roughly at the same time and a single attitudinal or behavioral preference is the dependent variable
Advanatages of Within - Groups Designs
- Participants in your groups are equivalent because they are the same participants and sevres as their own controls
- These designs give researchers more power to notice differences between conditions
- Within - groups designs require fewer participants than other designs
Power
Refers to the probability that a study will show a statistically significant result when a independent variable truly has an effect in the population
Order Effects
When being exposed to one condition affects how participants respond to other conditions (exposed to one condition exposed how other conditions react)
Practice Effects
- Which can happen when participants do better on a test due practice they have done
- Also known as fatigue effects
Carryover Effects
When there is a lasting effect that is being carried over one condition to another
Counterbalancing
- They present the levels of the independent variable to participants in different sequence
- In counterbalancing, any order effects should cancel each other out when all the data are collected
Full Counterbalancing
- When you are presenting all possible condition order (Which can be really easy)
- Complicated when there is more than 4 conditions
- Less complicated when there is 3 or less conditions
Example: A repeated - measures design with two conditions is easy to counterbalance because there are only two orders (A → B and B → A)
Parietal Counterbalancing
- Which only some of the possible conditions are represented
- One way to do it is to present the conditions in a randomized order for every subject
Example: Latin square
- A technique for partial counterbalancing
- A formal system to ensure that every condition appears in each position at least once
Disdavantage of Within - Groups Designs
- Potential for order effects (Solution: counterbalancing)
- Might not be practical or possible to counterbalance the order
- Experiencing all levels of the independent variable (IV) changes the way participants act (demand characteristics) (Solution: Asking the participants the purpose of the study)
Manipulation Check
- Is an extra dependent variable that researchers can insert into an experiment to convince them that their experimental manipulation worked
- Can help researchers determine whether the operationalization worked as intended
Pilot Study
- Simple study
- A test before you actually conduct the study with a small sample
- Used to confirm the effectiveness of their manipulation before using them in a target study
Cohen’s Guidelines for Effect Size Strength
d = 0.20
Described as small or weak
Comparable to an r of .10
d = 0.50
Described as medium or moderate
Comparable to an r of .30
d = 0.80
Described as Large or strong
Comparable to an r of .50
