DSRT 734 M50

INFERENTIAL STATISTICS FOR DECISION MAKING

Week-8 Discussions, Reflections, and Questions

Please discuss, elaborate, and reflect on the following questions from chapters 12 & 13

After reading your textbook, I want you to have a good understanding of the fundamentals of each chapter and show it to me.Please don't copy & paste from your textbook or some other online source. In other words, don't. You can read online material if it helps to understand the material, but you have

Chapter-12 topic Discussions and questions:

1.Can the repeated-measures ANOVA technique in can be used to analyze a design with only one independent variable?Explain your answer in detail.

It is not possible to to analyze a design with only one independent variable. The main reason is because repeated-measures ANOVA technique Repeated measures design uses the same subjects with each condition of the research, counting the control. For instance, repeated measures are collected in a longitudinal study in which alter over time is surveyed. Other considers comparing the same measure under two or more distinctive conditions. For occasion, to test the impacts of caffeine on cognitive work, a subject's math capacity may well be tried once after they devour caffeine and another time when they expend a fake treatment.

2.Is Tukey HSD test appropriate for data analyzed with a repeated-measures ANOVA?Explain your answer in detail.

Tukey HSD test compares the differences between means of values instead of comparing sets of values. The value of the Tukey test is given by taking the outright value of the contrast between sets of implies and isolating it by the standard blunder of the mean (SE) as decided by a one-way ANOVA test. The SE is in turn the square root of (change partitioned by test estimate). It is appropriate to use The Tukey HSD ("truly critical distinction" or "legitimate critical contrast") test could be a factual device utilized to decide in case the relationship between two sets of information is measurably critical - that's , whether there's a solid chance that an observed numerical alter in one esteem is causally related to an observed change in another esteem. In other words, the Tukey test could be a way to test exploratory speculation.

Data Set 12-1

Subjects

X₁

X₂

X₃

S

1

0

3

5

8

2

3

4

6

13

S

3

7

11

21

3.Calculate SS_tot using data set 12-1. Show all of your work.

4.Calculate SS_treat using data set 12-1. Show all of your work.

5.Developmental psychologists study children at different ages. In this study, the children were tested three times, at ages 5, 6 and 7. At each age, they worked a set of 25 problems. Each problem was a measure of the child's understanding of the concept of conservation (the concept that quantity remains the same despite changes in shape). The scores below represent percentage correct on the set of 25 problems. Calculate a repeated-measures ANOVA, Tukey HSD tests, and write an interpretation.

Age

Child

5

6

7

1

4

12

68

2

12

24

80

3

20

16

88

4

20

20

84

Chapter-13 topics Discussions and questions:

1.Explain the following terms

a)Factorial designs

b)Factor

c)Cell

d)Main Effect

e)Interaction

2.An F value of 2.75 was obtained when an interaction mean square was divided by an error mean square. The degrees of freedom were 6 and 18.If a = .05, is the null hypothesis for this interaction mean square (Ho: Interaction is significant)?Explain your answer.

3.Numbers in the cell in the following table are the means based on 8 scores for each cell.

A

A_l

A₂

A₃

B₁

10

20

30

B

B₂

40

50

60

B₃

50

30

10

Is the main effect of A appears to be significant?Explain your answer.

4.List the assumptions required for a factorial design ANOVA and explain each one.

5.To test some effects of layout design, participants spent the first part of an experiment reading the instructions on how to assemble a structure. The dependent variable was the number of minutes the participants spent reading the instructions before starting the assembly. The instructions were printed in small or large type with high contrast or low contrast.

Contrast

Low

High

Small

3

9

0

8

Type Size

2

7

Large

10

11

9

10

8

8

Construct an ANOVA summary table of results and state your conclusions about the effects of contrast and type size on reading time. Begin by listing the dependent and independent variables in this study.