Aice Psychology: Chapter 1.1: Experiments

Experiment

It is an investigation that looks for a cause and effect relationship in which the IV is manipulated and is expected to be responsible for the changes in the DV. The researcher produces 2 or more conditions.

-Example: An experiment can investigate whether the light level affects how well we concentrate

The Independent Variable

The variable in an experiment that is manipulated to create 2 or more conditions(levels) and is expected to be responsible for the changes in the DV.

-Example: (high or low light levels) or early and late in the day.

Dependent variable

The factor in an experiment that is measured and is expected to have changed due to the influence of the IV.

-Example: A test in the high light level and one in low light level

Extraneous variables

any variables other than the independent variable that seem likely to influence the dependent variable in all levels of the IV specific study. It is a variable that acts randomly

Experimental Condition

One or more of the situations in an experiment which represents different levels of the IV and are compared (or compared to a control condition).

-Example:( Bright and dull artificial lights) and (Artificial light compared to daylight-compared to control )

Control Condition

A level of the IV in an experiment where the IV is absent. It is compared to one or more experimental conditions

-Example: (Artificial light compared to daylight-compared to control )

Types of Experiments

-laboratory
-field
-natural

Laboratory Experiment

A research method in which there is a IV, DV, and strict controls It looks for a causal relationship and the setting is not in the usual environment for the participants with regard to the behavior they are performing.

Example: A lab experiment on the attention of schoolchildren in high and low light levels could be conducted. It might be investigated by testing the children on computerized attention task in a psychology room in a university.

Laboratory Experiment: pros and cons

Pros
- Allows researchers to have controls over all extraneous variables
- There will be standardization(each procedure will be same for everyone
-Standardization= better reliability
-Controlling variables= better validity
-Casual relationships can be determined through the repetition of the Experiment

Cons
-unrepresentative. The artificial situation can make participants behavior representative
-Demand Characteristics. Participants can change their behavior to fit the results that they think the investigators expect
- This reduces reliability and validity due to skewed responses

Field Experiment

An investigation looking for a casual relationship in which the IV is manipulated and is expected to be responsible for the changes to the DV. It is conducted in the normal environment for the participants for the behavior being investigated

Example: It like the Lab type except that the children are in their normal environment the classroom and are being tested on a usual behavior(the topic test).

Field Experiments: Pros and Cons

Pros
- More representative. Since the participants are more comfortable in their normal environment, they will act and respond normally making it more representative.
-Less Demand Characteristics. Since they aren't aware they're in an experiment, they won't be able to find of the experimental aims of the experiment
-Increased Ecological Validity because of its natural setting

Cons
-Extraneous Variables will be hard to control since it is not in a controlled environment(Lab).
-This lowers reliability and validity. The researcher won't be sure if the DV is caused by the changes of the IV as compared to a lab experiment
- Ethical issues may be raised since the participants aren't aware that they are in a study. It is hard to gain informed consent without giving the aims of the experiment and causing demand characteristics

Natural Experiment

An investigation looking for a casual relationship in which the IV is cannot be directly responsible for the changes to the DV. Instead they study the effect of an existing change or difference. Since the researcher can't manipulate the IV, its not a real relationship.

Example: Children attention could be measured on very dull and very bright days, when the light in the classroom differed( even with the light turned on). The DV could be measured with a class test

Natural Experiment: Pros and Cons

Pros
- This can be real world issues
-There is high ecological Validity due to the familiaty of the task and the setting making the results more true
The participants behavior will be more representative due to the nature of the setting
-Slim chance of demand characteristics since participants aren't aware they're in an experiment. Can't find out experimental aims

Cons
- Difficult to infer a cause and effect relationship due to lack of control and no manipulation of the IV
- Due to nature of experiment, there will be extraneous variables
-There is no controls or standardization so there can't be replication so reliability will be low
- Time consuming
- Only possible naturally

Experimental Design and the 3 Types

Experimental Design:The way participants are used in different levels of the IV. They may be allocated to all or only one level of the IV

3 Types
-Independent Measure Design
-Repeated Measure Design
-Matched Pairs designs

Independent Measures Design

An experimental design in which different groups of participants perform for each level of the IV(condition). It's called independent cause its not related to any other.

Independent Measures designs: Pros and Cons+ ways to deal with it

Pros
-Different participants are used in each level of Iv so no order effects.
-Participants only see one level of the IV so no demand characteristics
- Random allocation to the levels of the IV can reduce the effect of individual differences

Disadvantages
-Participant Variables can distort result if there
are important individual difference between different levels of the IV
- More participants are needed than in a repeated
-The study may be less ethical if participants are harmed and less effective if there's a small sample size b/c participants are hard to find.

Ways to deal with Cons (Random Allocation)
-To randomly allocation: 2 participants are given a number and the numbers are then divided into 2 groups
-This can be done by telling each participant a number, putting numbers in a hat, and drawing or 2 sets or using a random number generator(e.g) computer to do the same thing
-Random Allocation is used so participants are put in different levels of the IV and have an equal chance of being in any condition

Repeated Measures Designs

The same group of people participate in every level of the IV. The participants are repeating their performance under different conditions

Repeated Measures Design: Pros and Cons+ ways of dealing with it

Pros
- Participants variables are unlikely to distort the effect of the IV, as each participant does all levels
- Counterbalancing reduces the order effects
- Using less participants so goo when they are hard to find or when participants are at risk
- Each participant acts as their own baseline. Any differences between participants that could influence their performance to the DV will effect IV in both levels

Cons
- Order effects may occur and skew results
- Since participants see the experiment in all conditions demand characteristics will occur
-Repeated performance= Practice effects or Fatigue Effects.
- They can get worse or better with repeated performances.

Ways to deal with it( Counterbalancing)
Counterbalancing(ABBA Technique)
- The group of participants are divided into 2. ( Each possible order of the levels of the IV is performed by a different sub group of participants)
- Half will do M and N while the other half does N followed M

Matched Pair Designs

An experimental design in which participants are arranged into pairs. Each pair is similar in ways that are important to the study(age, IQ, gender, personality) and one member of each pair is used for each level of the IV.

Matched Pair Designs: Pros and Cons+ Ways to deal with it

Pros
- Since participants won't see the experiment in all conditions demand characteristics won't occur
-Participant variables aren't likely to effect the IV unlike the independent where individual differences are matched
- No order effects. By using different participants in each group this is avoided

Cons
-The availability of matched pair may be limited. Making the sample size small( although some studies conducted on twins use very large numbers of pairs
- Not practical. Finding almost identical participants are difficult. Fatigue effects may still occur.
- The right matching criteria has to be done in advance since the similarity between pairs is limited by the matching process

Ways to deal with it
- Identical twins can make ideal matched pairs since they are both genetically the same and are likely to have similar experiences

Types of Extraneous Variables

-Situational Variables
- Participants Variables
- Investigator Effects
- Demand Characteristics

Situational Variable

A confounding variable caused by an aspect of the environment.
-Can be reduced through standardization

Example: time of day, weather, noise, the type of room, the experiment takes place in, the amount of light or noise

Participant Variables

Individual differences which could affect their behavior in a study and therefore affect the IV. They could hide or exaggerate differences between levels of the IV
- Careful selections of the participants can reduce this.

Examples: IQ, age, and personality

Investigator Effects

These are the ways in which researchers may unwittingly unconsciously influence the results of the research and can be done in many ways:
- Physical appearance of the researcher such as age or gender
-Accent or tone
- Investigators may be unconsciously biased in their interpretation of data and find what they expect find

Can be reduced through a double blind test. This is when the participant nor the investigator know which condition the participant is in. For ex, the investigator wouldn't know which pill the participant took the placebo or the real drug

Demand Characteristics

Feature of the experimental situations which will give away the aims. They can cause participants to try to change their behavior, e.g to match their beliefs about what is supposed to happen, which reduces validity.

Order effects and the types

Practice and fatigue effects are the consequences of participating in a study more than once, e.g repeated measures designs, They can cause changes in performance between conditions that aren't due to the IV so can obscure the effect of the DV

Types
- Practice Effects
- Fatigue Effects

Practice Effects

A situation in which the participants performances improve because they experience the experimental task more the once due to familiarity or learning the task

Fatigue Effects

A situation in which the participants performances get worse because they experience the experimental task more the once due to bordom or tiredness

Ways to Reduce Order effects

-Random Allocation
-Counterblancing

Random Allocation

A way to reduce the effect of confounding variables such as individual differences.

Participants are put in each level of the IV such that each person has an equal chance of being in any condition.

Counterbalancing

Counterbalancing(ABBA Technique)
- The group of participants are divided into 2. ( Each possible order of the levels of the IV is performed by a different sub group of participants)
- Half will do M and N while the other half does N followed M

Stanadardisation

Participants receive the same instructions for the experiment as well as the experiencing the same procedures, scoring and even the environment will be identical.
-This is to ensure that any difference between participants or conditions are due to the variables under investigation rather than differences in the way they were treated.

Reliability

The extent to which a procedure, task, or measure is consistent
-For ex, that it would produce the same results with same people on each occasion

Validity

The extent to which the researcher is testing what they claim to be testing.

Ecological Validity

The extent to which a study is realistic or representative of real life.
The extent to which the findings of research in one situation would genralise to their situations. This is influenced by whether the situation(e.g Lab) represents the reals world effectively and whether the task is relevant ti real life( has mundane realism)

Generalise

Applying the samples findings of a study more widely, e.g to other settings and populations

Uncontrolled Variables

A confounding variable that may not have been identified and eliminated in an experiment which can confuse the results. It may be a feature of the participants or the situation

Confounding Variables

Extraneous factors that affect the performance of participants. In an experiment they would therefore affect scores on the DV and so obscure the IV.

Ethics in Experiments

- Informed Consent
- Right to Withdraw
- Privacy
- Confidentiality

Informed Consent

Knowing enough about a study to decide whether you want to agree to participate

Right to Withdraw

A participant should know that they can remove themselves, and their data, from the study at the any time

Privacy

Participants' emotions and physical space should not be invaded, for ex, they shouldn't be observed in situations or places where they would not expect to be seen

Confidentiality

Participants' result and personal information should be kept safely and not released to anyone outside the study

Hypothesis

A testable statement predicting a difference between levels of the IV( in an experiment) or a relationship between variables (in a correlation)

Directional(one-tailed) hypothesis

a statement predicting the direction of a relationship between variables,e.g in an experiment whether the levels of the IV will produce an increase or decrease in the DV or in a correlation whether an increase in one variable will be linked to an increase or a decrease in another variable
Ex. Produce the highest scores and in a correlational study whether there will be a positive or negative correlation

Non-Directional(two-tailed) hypothesis

statement of the relationship among two variables that does not predict the direction of the relationship

Ex: There will be a correlation between the number of computer games a student plays and their final A level grade

Null Hypothesis

the hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error. The alternative hypothesis is an alternative to the null hypothesis

Ex: There will be no relationship variable X and variable Y(or Any relationship between variable X and variable Y is due to chance)

Alternative Hypothesis

The testable statement which predicts a difference or relationship between variables in a particular investigation
Types are non directional and directional