#correlational

Experimental Studies:

-used to determine a cause-effect relationship (cause and effect relationship means whether A influences B or not; A could be like amount of milk drank each day, B could be height). So we want to see if drinking milk influences one height.

Two area must be fulfilled when performing experimental studies:

1: Manipulation of the independent variable

2: ensuring that participants in each experimental condition are equivalent to each other at the beginning of study; that they have equal chance of getting tested.

      This could be done through the following methods:

Random Assignment used if manipulation is between groups. For example, Girls and boys.

Counterbalancing: If manipulation is within group.

Question to consider: What are examples of when to use random assignment of counterbalancing?

The experimental group has to drink a certain amount of milk over a course of their life. Group 2, the control group does not drink milk.

Over time, we see if the average height of group 1 is any different from the average height of group 2. If yes, then we possibly have a causal effect.

Correlational Studies

-a statistical procedure used for determining whether or not there is a relationship between two variables.

- a major advantage of correlational studies is that they allow us to indentify relationships among variables as they occur naturally (no manipulation of the variables like done in experimental studies. 

-example of correlational studies  would be comparing people who likes to study with or without noise (music) with their extraversion or introversion.

-More examples:

  -comparison between self-esteem rated through S-data and O-data

  -achievement motivation and grade point average

  -self esteem and happiness

  -height and weight

  -extraversion and emotional stability

Terms related to correlational studies:

-Correlation coefficient (magnitude and direction to be considered)

Note: Correlational studies does not infer a cause-effect relationship (eg. because he/she's higher in self-esteem does not mean he/she's more happy)

This is because of two reasons:

 -Directionality Problem: Unlike experimental studies, we don't manipulate or try to change anything. As a result, when we compare something like self-esteem with happiness, we don't know for sure whether it is higher self-esteem that makes one more happy or the other way around; hence the term directionality problem).

-The Third Variable Problem: Something else could possibly be the result of the relationship; something else explains the relationship.

 Question to consider: When do we use correlation studies versus experimental studies designs?

Case Studies

-examining the life of one person in-depth (almost like an autobiography except you are trying to figure out about the how and why the person lived the way they did or come to be)

-method invented by Sigmund Freud (my favorite historical psychologists)

Advantages of case studies:

 -very in depth

 -provides insights into rare behaviors(such as multiple personalities and motivation for behaviours)

 -because it is very in depth, provides a rich source of hypothesis or research to do.

Disadvantages: 

-very time consuming (studying one person can be a lot of work)

-not generalizable (just because one person's motive for behaving a certain way does not mean everyone else is the same)

-researcher bias can arise (researcher may pay attention more to specific behaviour and ignore relevant ones; may pay more attention to certain details; may tweak the findings)

-subjectivity

-misinterpretion (if you're not very perceptive or knowledgeable yourself and can not reliably translate findings)

How to conduct

-through letters (so person being study mails letter to researcher for a period of time)

-by interviewing a bunch of people who knows the individual (almost like observer reports)

-interviews