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Lecture

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**preview**shows pages 1-2. to view the full**7 pages of the document.**Chp 12: B01 – Understanding Research Results: Desc and correlation

Statistics helps to develop an understanding of the collected data

Two reasons for using stats:

Describe data

Make inferences – in the basis of sample data about a population

Scales of measurement:

Whenever a variable is studied

oThere is an operational definition of the variable

oThere must be 2 or more levels of the variable

Recal from chapter 5

•The levels of a variable can be desribed using one of the

fourls scales of measurement

oNominal

No numerical or qunatative property

The lvls are just diffrn categories or groups

Most indepdent variables are nominal

Gender, eye color, marital status

oOrdinal

Minimal quantative distinction

We can rank the order the variable from

lowest to highest

Rank of the order of these problems

One problem with this time of level is we

don’t know the interval between them

Its like choclate is my most fav candy and

my second favoire it bubble gum – what is

the difference in liking them a lot ? a little ?

oInterval

Detailed qunatative properties

The intervals in between levlers are equal in

size

The difference btw 1and2 is the same as btw

2and3

Interval scales usually have 5+ quantativie

levels – very negative to very positive

Allow for more sophisticated statistical

treatments then ordinal scales

No absoloute zero point

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oRatio

Detailed qunatative properties

Equal intervals + absoloute zero point

Time weight length

The statistical analysis employed for interval and ratio variables is identical

Data can be summarized

oMean

oUtilizing a number

The scale used – dtrms the type of statistics that are appropriate – when the results

are analyzed

The meaning of a particular score on a variable dpnds

oOn the scale used

Analyzing the Results of Research investigations:

Most research focuses on the study of relationships between variables

Depdending on the way tat the variables are studied – there are 3 basic ways of

describing the results

oComparing group percentages

oCorrelating scores of iniduals on 2 variables

oComparing group means

Comparing group percentages:

Do more male or female like travel?

Correlating invidual scores:

You do no have distinct groups of subjects

Inviduals are measured on two variables – each variable has a range of

numberical values

Frequency Distributions:

Indicates the number of individuals that receive each possible score on a

variable

What can you discover by examining frequency distributions

oHow your participants responded

oShape of distribution

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