Chapter 16: Two Way ANOVA Flashcards

1
Q

The two way anova is a series of ___ which allow the effect of ___ IV to be investigated. The 2 way ANOVA is also called ___ or ___. Basically, this means that the effects of more than one __ can be examined in the same analysis.

A
  • F tests
  • two
  • factorial experiment
  • factorial design
  • IV
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2
Q

Definition of a factorial experiment ?

A

an experiment which the effects of two or more factors or IV are assessed in one experiment.

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3
Q

Give an example of the difference between One way and two way ANOVA’s (think variables)

A
One way: 
Dv: hours of sleep 
IV: exercise level ( light or heavy) 
----------------------
Two way: 
DV: hours of sleep 
IV: exercise level (light or heavy) 
time of day ( morning or evening )
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4
Q

We can get more ___ from the two way anova design. The two way ANOVA allows us to evaluate the effect of _______ IV on the DV in ___ experiment.

A
  • information
  • two
  • one single
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5
Q

Within the two way anova there are how many analyses?

A
  • 3
  • Effect of each Factor ( A and B)
  • effect of the interaction between factors
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6
Q

The effect of each IV is called what?

A
  • main effect
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7
Q

With the two way anova we can assess what

A
  • two main effects and an interaction effect
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8
Q

An interaction effect occurs when what?

A
  • when the effect of one factor is not the same at all levels of the other factor
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9
Q

We can get similar info if we did two separate one way ANOVAs but !?

A
  • we cannot determine an interaction effect between the two IVs on the DV…we can only determine each main effect of one factor at a time.
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10
Q
Graphs : 
- x axis= light and heavy exercise 
- y axis = hours of sleep 
- dotted line = evening 
- solid line = morning 
 L> solid line is perfectly horizontal the other is on a slight angle intersecting it but they are both equal length.  
- effect?
A

-no sig effect

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11
Q
Graphs : 
- x axis= light and heavy exercise 
- y axis = hours of sleep 
- dotted line = evening 
- solid line = morning   
L>both lines are perfectly horizontal going the same distance 
- solid is above  dotted 
- effect?
A
  • significant main effect in factor A, no other effect
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12
Q
Graphs : 
- x axis= light and heavy exercise 
- y axis = hours of sleep 
- dotted line = evening 
- solid line = morning   
L> both lines are on an angle in an increasing fashion...but both line up together pretty much exactly. 
effect?
A
  • significant effect in intensity of exercise …no other effect
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13
Q
Graphs : 
- x axis= light and heavy exercise 
- y axis = hours of sleep 
- dotted line = evening 
- solid line = morning  
L>  both line are parallel ...solid is above the dotted.... 
effect?
A

sig effect in intensity of exercise and time of day…no interaction

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14
Q

Graphs :

  • x axis= light and heavy exercise
  • y axis = hours of sleep
  • dotted line = evening
  • solid line = morning
  • solid line is increasing …dotted is decreasing
  • they intersect
  • effect ?
A
  • sig interaction effect but no other effect.
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15
Q
Graphs : 
- x axis= light and heavy exercise 
- y axis = hours of sleep 
- dotted line = evening 
- solid line = morning  
- dotted line is horizontal ....and below the dark line
- dark line is increasing 
effect?
A
  • sig time of day and interaction effect.
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16
Q

In a two way anova SS total is partitioned into what? (4)

A
  • SS rows
  • SS interaction
  • SS columns
  • SS within
    = SStotal
17
Q

What do you have to calc for two way anova? (15)

A
  1. SS row
  2. SS columns
  3. SS interaction
  4. SS within
  5. df rows
  6. df columns
  7. df interaction
  8. df within
  9. MS rows
  10. MS columns
  11. MS interaction
  12. MS within
  13. F rows
  14. F columns
  15. F interaction
18
Q

Two Way ANOVA Summary Table?

A
Source       SS     Df     MS     F        Sig
Factor A
Factor B
AxB
Within 
Total
19
Q

When looking at the sig column how do you know something is significant ?

A

If sig is greater than alpha it is not statistically significant

20
Q

Tukey HSD? How to?

A
  1. order means
  2. calc mean differences
  3. calc Q obt
    Qobt = Xi-Xj/ \/MSw/n
  4. compare Qobt to Q crit