Quiz 2 Flashcards
(31 cards)
What are the null hypotheses (one-way)?
- Ex:
- H(sub o): There is no statistically significant difference between the population means of males and females with regard to their GPAs.
- H(sub o): u(sub m) = u(sub f)
-With null hypothesis, you always state that there is no statistically significant difference.
What are the characteristics of Orthogonal Comparisons?
- A priori hypotheses
- ∑a(sub i) = 0 (valid comparison)
∑a(sub i)b(sub i) = 0 (independence) - Each comparison is on 1 degree of freedom
- You get as many comparisons as g-1 degrees of freedom
- Most powerful test of the three
- Significance level = alpha
What are the characteristics of Bonferroni?
- A priori hypotheses
- ∑a(sub i) = 0 (valid comparison)
Don’t need independence, so ∑a(sub i)b(sub i) does not have to equal 0 - Each comparison is on 1 degree of freedom
- You get as many comparisons as you want, but you lose power with each subsequent comparison
- Moderate power of the three
- Significance level = alpha/c (c is the number of comparisons)
What are characteristics of Scheffe?
- A posteriori or post hoc hypotheses
- ∑a(sub i) = 0 (valid comparison)
Don’t need independence, so ∑a(sub i)b(sub i)does not have to equal 0 - Each comparison is on the among degrees of freedom
- You can make as many comparisons as you want
- Lowest power of the three tests
- Significance level = alpha
What are experimentwise errors?
-Probability of making at least 1 Type I Error over the entire experiment (set of comparisons)
What are per comparison errors?
-Per Comparison Error: Probability of making a Type I Error for each individual comparison
What are the problems with multiple t-tests?
- Not okay for multiple t-tests because these are NOT independent and you’ve got an inflated Type I error rate
- You may find differences that may not even be there
What are the null hypotheses (two-way)?
- Ex:
1. H(sub o): There is no statistically significant difference between the population means of the massed practice and distributed practice groups with regard to stats test scores- H(sub o): u(sub m) = u(sub d)
- H(sub o): There is no statistically significant difference between the population means of the in-class and online teaching methods with regard to stats test scores.
- H(sub o): u(sub IC) = u(sub ON)
- H(sub o): There is no teaching method x (by) study habit interaction in the population.
What is a main effect?
- The overall difference among the levels of the independent variable tested
- Average of the simple effects
How many main effects in a specific design?
- The number of main effects is the number of independent variables that you have
- You have as many main effects as IVs
What is a simple effect?
- The effect of an independent variable at a single level of the other independent variable
- Lack of parallelism (do not cross)
- LOOK ON PAGE 11 OF NOTES
How many simple effects in a two-way design?
- The additive rather than the multiplicative
- Ex: 2x2 = 4
- Ex: 2x4 = 6
What is an interaction?
-The lack of parallelism in the simple effect
OR
-The effect of an independent variable differs depending upon the levels of the other IV
-If asked to define this, we have to define “simple effect” too
How do you plot an interaction? Graph form and in words.
- Choose an IV to place on the x-axis
- Values of the cell means go on the y-axis
- Plot a single curve for each level of the other IV
- MAKE HAND-WRITTEN NOTE CARD (Page 11)
What are range tests?
-All pairwise comparisons between means
- Tukey A
- Student Newman-Kewls
- Tukey B
What is the studentized range distribution?
-A sampling distribution of a t-test run between the largest and smallest means from a set of k means
How do you perform the Tukey A test?
- Order the means from smallest to largest
- Compute q for each comparison
- df(sub # of means, df error)
Compare each q with the critical values of q on the number of means and df error
How do you perform the SNK test?
- Order the means from smallest to largest
- Compute q for each comparison
- df(sub # of ordered means, df error)
Compare each q with the critical values of q based on the number of ordered means (or number of steps) and df error
*More power
How do you perform the Tukey B test?
- Order the means from smallest to largest
- Compute q for each comparison
- Average the critical values of the Tukey A and SNK for each comparison
How do you perform the Fisher-Hayter test?
- Order the means from smallest to largest
- Compute the q for each comparison
- df(sub # of means-1, df error)
Use the number of means - 1 and the df error to obtain the critical value of q
What was the rationale behind Duncan’s multiple range test and what are its problems?
- Rationale:
- Focused on trying to obtain greatest power possible
1. Experimentwise error rate similar to the orthogonal comparisons 1-(1-alpha)^g-1 – “protection level”
2. Step-down procedure similar to SNK
3. Derives out his own critical value tables
- Focused on trying to obtain greatest power possible
- Problems:
- Comparisons not independent
- Inflated Type I error rate; kind of like doing t-tests, so error rates go through the roof
The relationship between q and t?
- HAND-WRITTEN NOTE CARD (PAGE 13)
- Gosset and help forgot “2” when computing, which is why we have “t” and “q”
q(sub 2, infinity) = 2.77 (.05); 3.64 (.01) t(sub infinity) = 1.96 (.05); 2.576 (.01)
q=t x(times) square root of 2 t=q/2
Problem with unequal n with a one-way ANOVA?
-No problems mathematically, but you lose power.
What are the characteristics (coefficients) for orthogonal comparisons with unequal n?
- ∑n(sub i)a(sub i) = 0 (valid comparison)
- ∑n(sub i)a(sub i)b(sub i) = 0 (independence)
