Stats Year 2 - Woman

Question 1

The larger the sample the … the sampling error

Answer 1

Smaller

Question 2

The … variable is the variable measured to estimate the response.

Answer 2

Dependent variable

Question 3

Type I error

Answer 3

Rejecting H0 when it was correct.

Question 4

Type II error

Answer 4

Accepting H0 when it was incorrect.

Question 5

Correlation requires two variables that are?

Answer 5

Continuous

Question 6

Parametric tests assumme?

Answer 6

Normality

Question 7

Tests for normality

Answer 7

• Shapiro-Wilk
• Kolmogorov-Smirnov
• Anderson-Darling

(H0 for all is that the distribution is normal)

Question 8

One sample t-test

Answer 8

Compares a sample mean to a prestipulated value (population mean)

H0 is that the means are equal

Question 9

Result for one-tailed t-test
(t)

Answer 9

Values of t are normally distributed, so closer to 0 the closer the chance is to having the same mean
Distribution of t can be calculated using df of sample
Can be made non-directional by looking for the probability of the modulus of t

Question 10

Two sample t-test

Answer 10

Compares the means of two samples
H0 is that there is no significant difference between the samples.

Question 11

Univariate vs Multivariate

Answer 11

How many dependent variables are being analysed?
One or many?

Question 12

One way or multiple way?

Answer 12

How many independent variables are being used to test the dependent variables?
One or multiple?

Question 13

Independent or repeated measures

Answer 13

How many times is the same subject used?

Question 14

Assumptions of ANOVA

Answer 14

1. Normality
2. Homogeneity of variance
3. All data points are independent

Question 15

Normality in ANOVA

Answer 15

Assumes normality but fairly robust if sample sizes and variances are similar.
If not then use Kruskall-wallis

Question 16

Equation for one-way ANOVA

Answer 16

F = variance between group means / average variance within groups
If groups are from the same population F should = 1

Question 17

Hypotheses of one-way ANOVA

Answer 17

• Null hypothesis – population means are equal
• Alternative hypothesis – at least one mean is not equal.

Question 18

Tukeys HSD test

Answer 18

1. Post-Hoc test
2. Popular but conservative
3. Significant values are under 0.05

Question 19

R^2

Answer 19

Indicates how much of the variance in observations can be explained by the model

R = SS[between]/SS[total]

Question 20

SS

Answer 20

Sum of Squares = Sum (x-x(bar))^2

Question 21

Two-way ANOVA

Answer 21

Tests whether two factors affect the dependent variable independently or if they interact with each other

Question 22

Hypotheses of the two-way anova

Answer 22

Null 1: effect is the same height at all factor 1
Null 2: effect is the same height at all factor 2
Null 3: the effect of one factor is the same across all levels of the other factor.

Question 23

Scaling interaction

Answer 23

The magnitude of the effect of one variable depends on the strength of the other variable.

Question 24

Crossing interaction

Answer 24

the effect of one variable changes depending on the level of the other. The lines cross, indicating that the presence of both limits the effects of both.

Question 25

Analysis of Covariance ANCOVA

Answer 25

Used when we want to determine the effect of factors (discrete variables) and covariates (continuous variables) on dependent variables Improves detection of factors by removing variance (error)

Question 26

Covariate

Answer 26

A variable that you thought would affect the dependent variables, but you can’t manipulate, but you want to account for.

Question 26

Error Variability

Answer 26

Comes from the subject within group deviation from the mean of the group. Is smaller than the original error, uses the distance from regression line rather than from mean. It is calculated on the basis of the sum of squares.

Question 27

Assumptions of ANCOVA

Answer 27

1. Normality of treatment levels 2. Independence of variance estimates 3. Other same assumptions as with ANOVA 4. Linear regression of covariables 5. Linear regression is the same for both groups (homogeneity)

Question 28

In regression the residual sum of squares is...

Answer 28

... is based on the deviation of score from the regression line * The residual sum of squares will be smaller than the unadjusted sum of squares. * This regression shrinks the variance of each data group so that they can be compared better

Question 29

Fixed Effects

Answer 29

If I repeated the experiment would I use the same values? Values stated in the hypothesis.

Question 30

Random Effects

Answer 30

Exact values of this don't matter, we could use any of a selection. Look at changes over a range of temperatures for example.

Question 31

Why do random vs fixed effects matter?

Answer 31

In addition to the error in a test or model there is also error in the random sampling of temperatures for example. It will effect whether or not something is significant, software can be used to take this into account.