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Stats I Maastricht University > Task 5 > Flashcards

Task 5 Flashcards

1
Q

The samples in ANOVA are

a) dependent
b) independent

A

independent

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2
Q

In ANOVA normality is assumed, true or false?

A

true

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3
Q

How can we assume normality?

A

basic check - histogram

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4
Q

What to do if normality is violated

A

ensure samples are “large enough” -> CLT

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5
Q

Do we assume equal variances?

A

Yes

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6
Q

How do we check for equal variances?

A

Levene’s test

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7
Q

What to do if equal variances assumption is violated?

A

ensure sample size are “equally large”

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8
Q

Sum of squares?

a) SSG
b) SSW
c) SST

A

variation

a) between groups
b) within groups
c) total

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9
Q

Mean square?

A

average variation (variance)

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10
Q

Which sum of squares is for taking error into account?

A

SSW

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11
Q

Which df takes into df of erro?

A

DFW

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12
Q

What is a p-value in relation to ANOVA?

A

the probability of the F calculated or an even larger one if Ho is true

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13
Q

What does a one-way ANOVA enable us to compare?

A

2 or more independent samples

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14
Q

What is the general ANOVA model?

A

Yij = μ + ai + Eij

Yij: the individual score of a person j in group i

μ: the effect of constant factors (they are the same in every condition- its what all 3 samples have in common)

ai: the effect of the research factor (independent variable) e.g. no effect ai=0, increase in sales ai=+1
- > to calcualte group effect a1 = μ - ui (ui is the group mean)

Eij: the effect of remaining factors/effect of chance or individual differences aka “error” as they are not explicitly measured
-> to calculate Eij = Yij - ui (ui is the group mean)

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15
Q

The sum of all ai’s always equals

A

0

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16
Q

The sum of all Eij’s always equals

A

0

17
Q

How to calculate how much one person deviates in a population?

A

Yij - μ

18
Q

What acts as explained and unexplained variation?

A

explained - SSG

unexplained - SSW

19
Q

What is the Ho?

A

u1=u2=u3 (i.e. no group effect e.g. no influence on advertising)

20
Q

What is the Ha?

A

Not all u’s equal

21
Q

Does accepting Ha mean there is definitely effect from the dependent variable?

A

No there may be the effect of chance or error

22
Q

How can we determine normality? (only need to know about histograms)

A

Explore output

  1. Skewness = 0 if normal
    - > rule of thumb: the skewness of the sample can lie within -1 and +1 to e considered normal
    - > positive means skewed right and vice versa
  2. Kurtosis (flatess) = 0 if normal
    - > same rule of theumb
    - > positive means high point and vice versa
23
Q

What is always an unbiased estimator of the so-called error variance?

A

the variance within a group (MSW) is an unbiased estimator of error variance: the dispersion in the population due to remaining factors

24
Q

What is s^2p equal to in anova?

A

MSW

25
Q

What is the most efficient error estimate and why?

A

MSW/s^2p as they use all participants

26
Q

What is ALSO an unbiased estimator of error variance if Ho is true?

A

MSG as if the group means differ there is variance between the groups i.e. sampling error you may have just coincidentally picked more picky people for one sample

27
Q

What is the average value of the sampling distribution F?

A

1

28
Q

What is the expected value of F and why?

A

MSG and MSW are unbiased estimators of the same thing therefore should equal 1 however they are independent estimates so one time we draw the sample and MSG will be bigger than MSW

29
Q

When are BOTH MSG and MSW unbiased estimates of error variance?

A

when Ho is not true

30
Q

When do we reject Ho according to the F-statistic?

A

when it is larger than 1

31
Q

How do we find out which mean is different?

A

do the 3 possible t-tests and the p-values of each

then conduct bonferroni correction which divides the significance level by the number of comparions

compares the p-values to this p-value

32
Q

What does ANOVA compare?

A

The variability within groups vs between groups

33
Q

The larger the sample, the larger the ___

A

power

Stats I Maastricht University (5 decks)

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