An educational psychologist is examining response times to an on-screen stimulus. The researcherbelieves there might be a weak effect from age, but expects a more pronounced effect for differentcolor contrasts. She decides to examine a black on white (B/W) combination compared to 2alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (inmilliseconds):Color SchemeB/WR/WY/B22241033452121269.25211516-172235309.9.25182145223519213836925391433473030Age18-19352225153837174717133337284025254422281819192720-21163041211844142637254029Using MS Excel, conduct a 2-way ANOVA with a = 0.05. Fill in the summary table.The last column in the table below is read as, "Partial Eta-squared " and is a concept that wasNOT covered in the lectures. Partial 72 is used when there is a chance the data is not independent%3D21(click here to read more if interested ) Computing the values for "Partial nis not difficult. Simplydivide SSeffect by the sum of SSeffect and SSerror:. For example, Partial n (A) = SSA /(SSA + SSerror)%3DP-values should be accurate to 4 decimal places and all other values accurate to 3 decimal P-values should be accurate to 4 decimal places and all other values accurate to 3 decimalplaces.SourceSdfMSF-ratioP-valuePartial n?Age (A)2Color (B)Interaction (A × B)4Error63Provide the conclusions for this 2-way ANOVA.What is the conclusion regarding the main effect for age (A or rows):O There appears to be an effect due to age.O There is not enough evidence to reject the assumption that the marginal means across agegroups are equal.What is the conclusion regarding the main effect for color (B or columns):There appears to be an effect due to color.There is not enough evidence to reject the assumption that the marginal means across colorgroups are equal.What is the conclusion regarding an interaction effect between age and color (A x B):There appears to be an interaction effect between age and color.There is not enough evidence to reject the assumption of a lack of an interaction.

Name: An educational psychologist is examining response times to an on-scre
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Description: An educational psychologist is examining response times to an on-screen stimulus. The researcherbelieves there might be a weak effect from age, but expects a more pronounced effect for differentcolor contrasts. She decides to examine a black on whit

First Enter this data into Excel Now, Go to Data Tab Click on Data Analysis option Select Two…

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Statistics

An educational psychologist is examining response times to an on-screen stimulus. The researcher believes there might be a weak effect from age, but expects a more pronounced effect for different color contrasts. She decides to examine a black on white (B/W) combination compared to 2 alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (in milliseconds): Color Scheme B/W R/W Y/B 22 24 10 33 45 21 21 26 9 25 21 15 16-17 22 35 30 9. 9. 25 18 21 45 22 35 19 21 38 36 9. 25 39 14 33 47 30 30 Age 18-19 35 22 25 15 11 38 37 17 47 17 13 33 37 28 40 25 25 44 22 28 18 19 19 27 20-21 16 30 41 21 18 44 14 26 37 25 40 29 Using MS Excel, conduct a 2-way ANOVA with a = 0.05. Fill in the summary table. The last column in the table below is read as, "Partial Eta-squared " and is a concept that was %3D NOT covered in the lectures. Partial n2 is used when there is a chance the data is not independent (click here to read more if interested ) Computing the values for "Partial 7 21 is not difficult. Simply divide SSeffect by the sum of SSeffect and SSerror: For example, Partial 7²(A) = SSA /(SSA + Serror) P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal

An educational psychologist is examining response times to an on-screen stimulus. The researcher believes there might be a weak effect from age, but expects a more pronounced effect for different color contrasts. She decides to examine a black on white (B/W) combination compared to 2 alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (in milliseconds): Color Scheme B/W R/W Y/B 22 24 10 33 45 21 21 26 9 25 21 15 16-17 22 35 30 9. 9. 25 18 21 45 22 35 19 21 38 36 9. 25 39 14 33 47 30 30 Age 18-19 35 22 25 15 11 38 37 17 47 17 13 33 37 28 40 25 25 44 22 28 18 19 19 27 20-21 16 30 41 21 18 44 14 26 37 25 40 29 Using MS Excel, conduct a 2-way ANOVA with a = 0.05. Fill in the summary table. The last column in the table below is read as, "Partial Eta-squared " and is a concept that was %3D NOT covered in the lectures. Partial n2 is used when there is a chance the data is not independent (click here to read more if interested ) Computing the values for "Partial 7 21 is not difficult. Simply divide SSeffect by the sum of SSeffect and SSerror: For example, Partial 7²(A) = SSA /(SSA + Serror) P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Concept explainers

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.

Topic Video

Question

An educational psychologist is examining response times to an on-screen stimulus. The researcher
believes there might be a weak effect from age, but expects a more pronounced effect for different
color contrasts. She decides to examine a black on white (B/W) combination compared to 2
alternatives: red on white (R/W) and yellow on blue (Y/B). Here is the data for response times (in
milliseconds):
Color Scheme
B/W
R/W
Y/B
22
24
10
33
45
21
21
26
9.
25
21
15
16-17
22
35
30
9.
9.
25
18
21
45
22
35
19
21
38
36
9
25
39
14
33
47
30
30
Age
18-19
35
22
25
15
38
37
17
47
17
13
33
37
28
40
25
25
44
22
28
18
19
19
27
20-21
16
30
41
21
18
44
14
26
37
25
40
29
Using MS Excel, conduct a 2-way ANOVA with a = 0.05. Fill in the summary table.
The last column in the table below is read as, "Partial Eta-squared " and is a concept that was
NOT covered in the lectures. Partial 72 is used when there is a chance the data is not independent
%3D
21
(click here to read more if interested ) Computing the values for "Partial n
is not difficult. Simply
divide SSeffect by the sum of SSeffect and SSerror:. For example, Partial n (A) = SSA /(SSA + SSerror)
%3D
P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal

P-values should be accurate to 4 decimal places and all other values accurate to 3 decimal
places.
Source
S
df
MS
F-ratio
P-value
Partial n?
Age (A)
2
Color (B)
Interaction (A × B)
4
Error
63
Provide the conclusions for this 2-way ANOVA.
What is the conclusion regarding the main effect for age (A or rows):
O There appears to be an effect due to age.
O There is not enough evidence to reject the assumption that the marginal means across age
groups are equal.
What is the conclusion regarding the main effect for color (B or columns):
There appears to be an effect due to color.
There is not enough evidence to reject the assumption that the marginal means across color
groups are equal.
What is the conclusion regarding an interaction effect between age and color (A x B):
There appears to be an interaction effect between age and color.
There is not enough evidence to reject the assumption of a lack of an interaction.

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