Lecture 9 Flashcards by Kylie hinde

A Scattergram plots each participants score on the

Independent variable against the dependent variable

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In a Scattergram the dependent variable goes on which axis?

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There are 3 types of relationships found in scattergrams

Linear
Curvilinear
None

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Correlation and linear regression can only be used for this type of Scattergram relationship

Linear or straight line relationship

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Pearson correlation will only tell you if you have a ……type of relationship

Linear

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If you have no linear relationship looking at a Scattergram what can’t you do?

Pearsons correlation

Linear regression

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What’s the next step afte funding a linear relationship in your Scattergram?

You superimpose a line of best fit also called the regression line

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Regression line best represents the

Relationship between the 2 varables

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Regression line tells you if

Y can be predicted on X

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Independent variable always goes on which axis?

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Where can the effect size be found in a Scattergram in SPSS??

Top right corner where it says R2 linear = ……

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Effect size is the….

Correlation of the two variables squared

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In a Scattergram you’re looking for a line of best fit that is….

On an angle

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If line of best fit is on an angle it means….

There is a relationship!!!

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What does the Scattergram look like if there is no relationship??

Flatline/horizontal

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Relationship is not strong when points are

Scattered all around Scattergram

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5 points to think about with a Scattergram…

Type of relationship
Direction
Cluster
Gaps
Outliers

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The easiest way to work out if two variables are related is by plotting them on a

Scattergram

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What does direction of relationship refer to on a Scattergram?

Positive or negative

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Type of relationship in a Scattergram refers to

Linear etc?

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A line that goes up towards the right on a Scattergram is what type of relationship?

Positive - as one variable increases so does the other…

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If the line goes up to the left of the Scattergram the relationship between variables is

Negative - as one variable increases the other decreases

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Y stands for which variable?

Dependent

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X is what variable?

Independent

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Gaps in the data suggest the existence of

Sub samples in the data

An R2 of 0 or similar on a Scattergram means that there

Is no linear relationship between the varables

What is covariance?

How two variables vary together

If we want to see if there is a relationship between 2 variables we are actually interested in whether

Changes in one variable are met with changes in another variable

In covariance...When one variable deviates from it's mean we would expect

The other variable to deviate from it's mean in a similar way

To calculate the exact similarity between the pattern of differences in covariance we calculate the...

Cross-product deviations

When calculating variance essentially what you're looking at is how

Each score deviates from it's mean

To get an average of the combined differences for the two variables you need to:

Sum the cross products | Divide by the number of cases minus 1

Covariance formula:

CPF = (X - M2) (Y - M2)

Covariance mean of two different variables formula:

CovXY = Sum of [(X - Mx) (Y - My)] / N -1

Degrees of freedom (N -1) give you

An unbiased estimate

Covariance problem is that it depends on

The scales of measurement you're using - it's not a standardised measure

Need to convert covariance into a set of standard set units to be able to

Compare it

Covariance is converted to standard units by computing the

Pearsons r

Pearsons r is most common in measuring

Association between two variables

What type of scale do you need at least to use pearsons r?

Interval scale

Interval scale means

Equal differences (1-2-3-4-5) with no true 0

Ordinal scale is

Rank order - has no 0. Goes from smallest - biggest

Nominal data is

Grouping data, data in categories. Numbers mean group names etc

Pearsons r is the

Standardised covariance between two variables

Pearson r formulae is

r = covXY / SxSy

Pearsons r will only tell you about what sort of relationship?

Linear!!!

Pearsons r can range from

-1 (strong neg) to +1 (strong pos)

What is a weak pearsons r (correlation only!!)

0-0.29

A moderate pearsons r is (correlation only!!)

0.30-0.59

A strong pearsons r is (correlation only!!)

0.60-1.00

Pearsons r does not reveal

Causality

Pearsons r sig (effect size)

At .05

Usually R2 converted to a

Weak effect size

``` r = .10 R2 = .01 ```

Medium effect size

``` r = .3 R2 = .09 ```

Strong effect

``` r = .5 R2 = .25 ```

3 factors that influence the size of Pearson correlation

Sample size Restriction of range or variability Use of heterogeneous sub samples

There are 2 mathematical assumptions for pearsons r

Interval scale data | Normality

What is particularly bad for correlation and regression?

Outliers!

A partial correlation is where there is

Overlapping variance - or how much variance is commonly shared by all variables

A partial correlation will Allow you examine the relationship between

2 variables when the 3 has been removed

Two types of partial correlation

Semi partial | Partial

Semi partial correlation will only remove the effect of the 3rd variable

Only from the independent variable

Partial correlation will remove the effect of the 3rd variable from

Both other variables

Partial correlations give us a more

Accurate reflection of the relationship between two variables

Partial correlations also tell us what variables

Shouldn't go in the model together

Why is partial correlation important?

We want to account for as much variance as possible!

Doing a partial correlation helps you work out if you have

Multicollinearity between your variables

Multicollinearity is where the overlap

Between variances is considerable

You know if you have multicollinearity with 2 things

Pearsons r correlations exceed absolute value if .6 Or .8 with Field

What correlation techniques do you use if your variables aren't interval scale but categorical?

Chi squared Phi Cramer's V Cohens kappa

What correlation techniques do you use if your variables aren't interval scale but ranked or ordinal data?

Spearman rank | Kendalls W

What correlation techniques do you use if your variables aren't interval scale but categorical and interval data

Eta | Point biserial

Is chi square non parametric or parametric?

Non-parametric

Chi squares used in 2 situations...

To compare groups on one nominal/categorical variable | To determine if there is a relationship between 2 variables that are both nominal/categorical

Pearson called the chi square test a

Goodness of fit

Chi square called goodness of fit because it determines if there is a good fit between

``` The data (observed frequencies) What would be expected from theory (expected freq) ```

df - in a 2x2 table, df would =

(2 - 1) (2 - 1) = 1*1 = 1

Chi square can be used when nominal/categoric variables have been measured on how many levels?

2 or more

Chi square does not indicate

Strength OR relationship between variables

Phi used for a

2x2 contingency tables

2 methods to determine effect size in chi square analysis

``` Cramers v (most common) Odds ratio ```

Cramers v measure of effect size for weak, mod, strong are

.1 .3 .5

Chi square has 2 mathematical assumptions:

Independence of observations (diff ppl in each of your groups and only tested once) Expected cell frequencies must exceed 5