Z Scores, t-tests, 1-Way-ANOVA

Question 1

Briefly, what is the z-score?

Answer 1

Where all normal distributions are the same.

Question 2

How is the z-score calculated,

Answer 2

The mean is subtracted (so it equals 0) and that is divided by variance (so SD is 1).

Question 3

What is the main problem with z-scores?

Answer 3

They require us them know the sample parameters mean and SD.

Question 4

The t-distributions is (more/less) spread out then the z-distribution.

Answer 4

More.

Question 5

What does the spread of the t-distribution depend on?

Answer 5

The uncertainty of the estimates of the mean and SD.

Question 6

How is SEM directly calculated?

Answer 6

Use lots of sample estimates of the mean and calculate the variance.

Question 7

How is SEM indirectly calculated?

Answer 7

Divide the standard deviation of the sample by the square root of n.

Question 8

What is the main question in t test 1?

Answer 8

Is the sample mean the same as the hypothesised population mean?

Question 9

What is t in t test 1?

Answer 9

Distance between sample and hypothesised men’s divided by SEM.

Question 10

Why is a degree of freedom lost in t test 1?

Answer 10

Because an estimate of the sample mean is being used.

Question 11

What is the main question in t test 2?

Answer 11

Are the means of two samples the same?

Question 12

How is whether u1 = u2 assessed in t test 2?

Answer 12

Look at how many SDs data points are apart.

Question 13

How is t calculated in t test 2?

Answer 13

Using the standard deviations of the differences between the two means.

Question 14

What is generally used to assess and deal with homoscedasticity?

Answer 14

Levene’s test, then if p<0.05, use Satterwaithe’s correction.

Question 15

What is the main question in t test 3?

Answer 15

Is the mean difference of scores 0?

Question 16

How do all t tests express a difference between means?

Answer 16

As SEM: the number of SDs from the mean.

Question 17

Give 2 limits of t tests.

Answer 17

They assume normal distributions and they can only compare 2 means.

Question 18

In 1-way ANOVA, what is a direct estimate of the variance between means?

Answer 18

Calculate variance from the observed means.

Question 19

In 1-way ANOVA, what is an indirect estimate of the variance between means?

Answer 19

Calculate the SEM*2, which is the expected variance based on the spread of the individual data points about their mean.

Question 20

If an IV does not influence a DV, the direct and indirect estimate should be (the same/different).

Answer 20

The same.

Question 21

If an IV does influence a DV, the direct and indirect estimate should be (the same/different).

Answer 21

Different.

Question 22

In 1-way ANOVA, what makes up the observed value?

Answer 22

Grand mean + level effect + error.

Question 23

What is the sum of squares between?

Answer 23

The variability between level means (direct method).

Question 24

What is the error sum of squares?

Answer 24

The variability due to noice (indirect method).

Question 25

What ratio is ANOVA looking at?

Answer 25

The observed level effects to that expected from the error.

Question 26

What is effect size?

Answer 26

The proportion of total variability explainer by knowing which level data belongs to.

Question 27

What is R squared?

Answer 27

The proportion of variance explained in the experiment.

Question 28

What is adjusted R squared?

Answer 28

The estimated proportion of variance in the population that level is likely to explain.

Question 29

In 1-way ANOVA, how is partial Eta-squared used?

Answer 29

To refer to the proportion of variance in the data explained by a factor of an interaction.

Question 30

In 1-way ANOVA, how is R squared used?

Answer 30

To refer to the promotion of variance explained by all factors and interactions.