student submission -- gen psych methods and tools of study in psych

7/28/2019 Student Submission -- Gen Psych Methods and Tools of Study in Psych

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Methods



Qualitative

Method



oQualitative

Methods

• as the name indicates,

are methods that do not

involve measurement or statistics



oExample of

Qualitative MethodCase study

méthode clinique or clinicalmethod. introspection

naturalistic observation Interviewingphenomenological

methods.



Case Study One qualitative method that goes

back a long way

Physicians like Sigmund Freudbecame interested in psychologicalproblems, they continued their tradition of writing and publishing

descriptions of their most interestingpatients, the treatments theyattempted to use, and the progress of

the disorder.



Méthode Clinique

particularly well used by Jean Piagetand his followers.

The basic idea is to present aperson with a situation or problemfor them to deal with. The

researcher observes how theyhandle the situation and asks themquestions to try to understand the

thought processes they are using.



Another version of the Méthode

Clinique is called experimentalphenomenology.

One study, for example, asked

chess masters and novices to

think out loud while playingchess, and analyzed the

differences in approach.



Introspection Methodintrospection used by Wilhelm Wundt

often considered the founder of scientific

psychology -- and his students.

Researchers paid careful attention to

their own perceptions of simple events

like colors, and noted changes in their perceptions following changes in the

events.



Naturalistic Observation

Probably the oldest qualitative methodis to step back from the situation and

make every effort not to interfere.

A variation on naturalistic observationused by some sociologists andpsychologists is called participantobservation. A sociologist who is

interested in studying the lifestyles of people in some subculture (say amotorcycle gang) may actually join thesubculture and interact with the people



•Interviewing MethodOne of the most useful qualitative

techniques

It is often a part of all of the preceding

methods.

Contrary to what many people believe,

interviewing is not easy. In fact, it is a rare

person who is truly skillful at

interviewing. You have to make sure youare not leading the person in the direction

you would like them to go. You have to

make sure you don’t misinterpret what they



Phenomenological

Methods Phenomenology is the study of the

contents of consciousness phenomena

and phenomenological methods are ways

of describing and analyzing these

contents.

used in psychology to refer to subjective

experiences or their study

Originally, the methods focused on

describing one’s own thought, feelings,

and perceptions.



Correlation



Correlation

is what you are doingwhen you compare two

sets of measurements

(each set is called a

variable).



If you were to measure everyone’sheight and weight, you could then

compare heights and weights and see if they have any relationship to each other -- any "co-relation," if you will. Of course, the taller you are, generally

speaking, the more you weight. But it isobviously not a perfect co-relation,because some people are thin andsome are fat.

A perfect correlation is +1. Very close toperfect would be a comparison of men'sshoe size and their... foot length. For

example, here is some data

F t l th



Shoe size

Foot length

(inches)

John 4 1/2 9 1/4

Dave 5 9 3/8

Sam 5 9 1/4

Jim 6 1/2 9 1/2

Ed 6 1/2 9 3/4

Bob 7 9 3/4

Ted 8 10 1/8

Matt 11 1/2 11

Damian 12 11 1/4

Horton 14 11 3/8



This is called a scatter plot. The line

is the line that describes the "best fit"-- in other words, it accounts for the

data most nicely. But you can see by

comparing the dots to the line, it'spretty close to a +1 correlation.

Most things have a correlation of

0. An example would be your shoesize vs. your SAT score.

homicide rates ith hand g n



homicide rates with hand gun

ownership. (The figures from 1980's.)Country Homicide rate (per

100,000 per year)

Hand gun ownership (%

of population)USA 8.8 29.0%

Northern Ireland 5.2 1.5%

Finland 2.9 7.0%

Canada 2.1 4.0%

Australia 2.0 2.0%

Scotland 1.8 0.5%

Belgium 1.8 6.0%

Switzerland 1.2 14.0%

Norway 1.2 3.5%

France 1.2 5.5%

West Germany 1.2 6.5%

Spain 1.0 2.0%

The Netherlands 0.9 1.0%

England and Wales 0.7 0.5%



Scatter plot



This will give you a number thattells you how much of the

variance (variation) in one or theother of the variables is"explained" by the other. So, for example, the .70 correlation

above tells us that 49% of thevariation in homicide rates isrelated to the ownership of handguns. That leaves us with 51% of the variation we still need toaccount for.

I h l ll



In psychology, we are generallyimpressed by correlations of .3 andhigher. .8 or .9 blows us away. But

one thing correlation cannot tell youis causality. Your grades and your SATs correlate pretty well Even thehomicide-hand gun example doesn't

give you causation. Odds are alwaysthat there is something else thatcauses two things to

correlate. Maybe a violent cultureleads to both more guns and moreviolence. It takes other kinds of research most especially experiments

to pin down cause and effect!



Descriptive

Statistics



Descriptive Statisticsare ways of summarizing large sets of

quantitative information. If you havea large number of measurements, thebest thing you can do is to make a

graph with all the possible scoresalong the bottom, and the number of times you came across that scorerecorded vertically in the form of abar. But such a graph is just plainhard to do statistical analyses with,so we have other, more numericalways of summarizing the data.



Example

John -- 3.0Mary -- 2.8George -- 2.8Beth -- 2.4Sam -- 3.2

Judy -- 2.8Fritz -- 1.8Kate -- 3.8Dave -- 2.6Jenny -- 3.4Mike -- 2.4Sue -- 4.0Don -- 3.4Ellen -- 3.2Orville -- 2.2



en raTendency

Central tendency refers to the idea that there isone number that best summarizes the entireset of measurements, a number that is in someway "central" to the set.

The mode. The mode is the measurement thathas the greatest frequency, the one you foundthe most of. Although it isn't used that much,

it is useful when differences are rare or whenthe differences are non numerical. Theprototypical example of something is usuallythe mode.

The mode for our example is 3.2. It is the

grade with the most people (3).

Th di Th di i th b



The median. The median is the number

at which half your measurements are

more than that number and half are less

than that number.The median is actually a better measure

of centrality than the mean if your data

are skewed, meaning lopsided.The median for our example is 3.0. Half

the people scored lower, and half higher

The mean. The mean is just the

average. It is the sum of all your

measurements, divided by the number

of measurements.



This is the most used measure of central

tendency, because of its mathematical

qualities. It works best if the data isdistributed very evenly across the range,

or is distributed in the form of a normal

or bell-shaped curve One interestingthing about the mean is that it

represents the expected value if the

distribution of measurements were

random! Here is what the formula looks

like:



So 3.0 + 2.8 + 2.8 + 2.4 + 3.2 + 2.8 + 1.8 + 3.8+ 2.6 + 3.4 + 2.4 + 4.0 + 3.4 + 3.2 + 3.2 is

43.8. Divide that by 15 and that is the mean or

average for our example: 2.92



Statistical dispersion Dispersion refers to the idea that there is a

second number which tells us how "spread out"all the measurements are from that centralnumber.

The range. The range is the measure from thesmallest measurement to the largest one. Thisis the simplest measure of statistical dispersionor "spread."

The range for our example is 2.2, the distancefrom the lowest score, 1.8, to the highest, 4.0.



Interquartile range. A slightly moresophisticated measure is the interquartilerange. If you divide the data into quartiles,

meaning that one fourth of the measurementsare in quartile 1, one fourth in 2, one fourth in3, and one fourth in 4, you will get a number that divides 1 and 2 and a number that divides

3 and 4. You then measure the distancebetween those two numbers, which thereforecontains half of the data. Notice that thenumber between quartile 2 and 3 is themedian!

The interquartile range for example is .9,because the quartiles divide roughly at 2.45and 3.35. The reason for the odd dividing linesis because there are 15 pieces of data, which,

of course, cannot be neatly divided into

The standard deviation The standard



The standard deviation. The standard

deviation is the "average" degree to

which scores deviate from the

mean. More precisely, you measure howfar all your measurements are from the

mean, square each one, and add them

all up.The result is called the variance. Take

the square root of the variance, and you

have the standard deviation. Like themean, it is the "expected value" of how

far the scores deviate from the

mean. Here is what the formula looks

like:



So, subtract the mean from eachscore and square them andsum: 5.1321. Then divide by 15and take the square root and youhave the standard deviation for our

example: .5849.... One standarddeviation above the mean is atabout 3.5; one standard deviationbelow is at about 2.3



The Normal CurveThis curve, also called the bell-shaped curve,

represents a distribution that reflects certainprobabilistic events when extended to aninfinite number of measurements. It is an

idealized version of what happens in many largesets of measurements: Most measurements fallin the middle, and fewer fall at points farther away from the middle. A simple example isheight: Very few people are below 3 feet tall;very few are over 8 feet tall; most of us aresomewhere between 5 and 6. The same appliesto weight, IQs, and SATs! In the normalcurve, the mean, median, and mode are all the

same.



One standard deviation below the meancontains 34.1% of the measures, as does

one standard deviation above themean. From one to two below contains13.6%, as does from one to twoabove. From two to three standarddeviations contains 2.1% on each end. Another way to look at it: Between onestandard deviation below and above, wehave 68% of the data; from two below totwo above, we have 95%; from three below

to three above, we have 99.7%

Because of its mathematical



Because of its mathematical

properties, especially its close ties to

probability theory, the normal curve

is often used in statistics, with the

assumption that the mean and

standard deviation of a set of

measurements define thedistribution. Our example above is a

clear example - a normal curve with a

mean of 2.92 and a standarddeviation of .58 is quite different from

the pattern of the original data.



A good real life example is IQ

and intelligence: IQ tests are

intentionally scored in such a

way that they generate a

normal curve, and because IQtests are what we use to

measure intelligence, we often

assume that intelligence isnormally distributed, which is

not at all necessarily



Experiments



Experiments

A simple experiment starts outvery much like correlation: You

have two sets of measurements

and you look to see if there is arelationship between

them. You want to know if they

"co-relate." The two sets of

measures are called variables.



The big difference betweenexperiments and correlations is that,

in experiments, you actuallymanipulate one of the variables. If you are manipulating one of thevariables, that means that the second

variable, if it "co-relates," was causedto do so by the variable youmanipulated! You can tell what thecausal effects of the first variable areon the second one -- something youcan never be quite sure of with aregular correlation study.



Two Variables in

ExperimentsIndependent Variable-the one that

you manipulate

Ex: Think of it like a radio knob: You

can turn the knob because it is, to adegree, independent of the rest of the

radio

Dependent Variable- The other variable

Ex: Like the volume of your music

depends on where you set the volume



END!

student submission -- gen psych methods and tools of study in psych

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