Solved by verified expert:Write a 2- to 3-paragraph analysis of your one-way ANOVA results for
your research question. Include any post-hoc tests with an analysis of
the strength of any relationship found (effect size). Also, in your
analysis, display the data for the output. Based on your results,
provide an explanation of what the implications of social change might
be.Use proper APA format, citations, and referencing for your analysis, research question, and display of output.I am attaching an example of a perfect paper to help guide you. It is called WK7Assgn1-example-1.docxI am also attaching the notes from my one-way anova test which will be what you need to write the paragraph. It is called week7.docxI am also going to attach a small video from the professor with some good notes on how to word. It is called WAL_RSCH8210_07_A_EN-DL.zip
wal_rsch8210_07_a_en_dl.zip
week7.docx
wk7assgn1_example_1.docx
Unformatted Attachment Preview
One way anova is a comparison of means test across a factor.
Dependent variable is age
ANOVA
Q1. Age
Between
Groups
Within Groups
Total
Sum of
Squares
14489.903
10626193.940
10640683.840
df
4
50311
50315
Mean
Square
3622.476
F
17.151
Sig.
.000
F
17.151
Sig.
.000
211.210
Test of
Homogeneity
of Variances
Q1. Age
Levene Statistic
7.959
df1
4
df2
50311
Sig.
.000
ANOVA
Q1. Age
Between
Groups
Within Groups
Total
Sum of
Squares
14489.903
10626193.940
10640683.840
df
4
50311
50315
Mean
Square
3622.476
211.210
Post Hoc Tests
Multiple Comparisons
Dependent Variable: Q1. Age
Bonferroni
(I) Q3a.
Country’s
present
economic
condition
Very Bad
Fairly bad
(J) Q3a.
Country’s
present
economic
condition
Fairly bad
Neither
good nor
bad
Fairly good
Very good
Very Bad
Neither
good nor
bad
Fairly good
Very good
95%
Confidence
Interval
Mean
Difference
(I-J)
.781*
1.265*
Std.
Error
.174
.205
Sig.
.000
.000
Lower Bound
.29
.69
Upper
Bound
1.27
1.84
1.397*
.880
-.781*
.485
.183
.330
.174
.201
.000
.077
.000
.160
.88
-.05
-1.27
-.08
1.91
1.81
-.29
1.05
.616*
.099
.179
.327
.006
1.000
.11
-.82
1.12
1.02
Neither
good nor
bad
Fairly good
Very good
Games-Howell
Very Bad
Fairly bad
Neither
good nor
bad
Fairly good
Very good
*. The mean difference is significant at the
0.05 level.
Very Bad
Fairly bad
Fairly good
Very good
Very Bad
Fairly bad
Neither
good nor
bad
Very good
Very Bad
Fairly bad
Neither
good nor
bad
Fairly good
Fairly bad
Neither
good nor
bad
Fairly good
Very good
Very Bad
Neither
good nor
bad
Fairly good
Very good
Very Bad
Fairly bad
Fairly good
Very good
Very Bad
Fairly bad
Neither
good nor
bad
Very good
Very Bad
Fairly bad
Neither
good nor
bad
Fairly good
-1.265*
-.485
.132
-.386
-1.397*
-.616*
-.132
.205
.201
.209
.345
.183
.179
.209
.000
.160
1.000
1.000
.000
.006
1.000
-1.84
-1.05
-.46
-1.35
-1.91
-1.12
-.72
-.69
.08
.72
.58
-.88
-.11
.46
-.517
-.880
-.099
.386
.332
.330
.327
.345
1.000
.077
1.000
1.000
-1.45
-1.81
-1.02
-.58
.42
.05
.82
1.35
.517
.781*
1.265*
.332
.173
.206
1.000
.000
.000
-.42
.31
.70
1.45
1.25
1.83
1.397*
.880
-.781*
.485
.184
.348
.173
.201
.000
.084
.000
.111
.90
-.07
-1.25
-.06
1.90
1.83
-.31
1.03
.616*
.099
-1.265*
-.485
.132
-.386
-1.397*
-.616*
-.132
.178
.345
.206
.201
.210
.362
.184
.178
.210
.005
.999
.000
.111
.971
.825
.000
.005
.971
.13
-.84
-1.83
-1.03
-.44
-1.37
-1.90
-1.10
-.70
1.10
1.04
-.70
.06
.70
.60
-.90
-.13
.44
-.517
-.880
-.099
.386
.350
.348
.345
.362
.578
.084
.999
.825
-1.47
-1.83
-1.04
-.60
.44
.07
.84
1.37
.517
.350
.578
-.44
1.47
Running head: TESTING FOR ONE-WAY ANOVA
Testing for One-Way ANOVA – Week 7 Assignment 1
Walden University
1
TESTING FOR ONE-WAY ANOVA
2
Testing for One-Way ANOVA – Week 7 Assignment 1
Example Research Question, One-Way ANOVA, and Analysis
The following will examine an example research question from the High School
Longitudinal Study 2009 Dataset: Is there a relationship between school locale and the number
of AP Courses offered to their respective students? This research question would align with a
quantitative method as it is strictly looking at data (whether or not there is a
relationship/differences) and does not seek to address any reasons as to why differences is exist,
if they should, or aim to implement new policies at this time. A One-Way ANOVA was
conducted (Figure 3) using the two variables of “school locale” and “number of AP courses
offered” as the independent and dependent variables, respectively, with school locale being a
nominal measurement and number of AP courses being a ratio measurement (FrankfortNachmias & Leon-Guerrero, 2015; Laureate Education, 2016h; Wagner, 2016). The null
hypothesis is that there are no significant statistical differences in the number of AP courses
offered based on the school’s locale.
The null hypothesis was rejected as statistical significance was found at p = 0.000, below
the typical alpha threshold of 0.05 (Frankfort-Nachmias & Leon-Guerrero, 2015; Laureate
Education, 2016h; Wagner, 2016). The F critical value was found at 2.61, calculated by SPSS to
be 632.698, again supporting a strong level of statistical significance and safely rejecting the null
hypothesis. A test of homogeneity was conducted (Figure 2) and significance was found at
0.000; therefore, equal variances were not assumed and a Games-Howell Post-Hoc (Figure 4)
was used to address the levels of statistical significance between and within groups. In viewing
the Post-Hoc, there are significant statistical differences among and between each of the four
groups (city, suburb, town, rural) as statistical significance was found at 0.00 across the board.
TESTING FOR ONE-WAY ANOVA
3
In addressing the descriptive data (Figure 1), schools located in a suburb offer the highest
amount of AP courses followed by city, rural, and town locales in order of highest to lowest.
In addressing the real world practicality and meaningfulness, effect size was calculated
using the eta square (Frankfort-Nachmias & Leon-Guerrero, 2015; Laureate Education, 2016h;
Wagner, 2016). Taking the between groups variance (64688.889) and dividing it by the total
group variance (650745.306) the effect size came to 0.099, a small effect size indicating
approximately 9.9% of the variance among the number of AP courses offered is attributable to
school locale. This small effect size, in the light of a strong statistical significance being found,
indicates that there are other variables which may more strongly account for the statistical
differences regarding the number of AP courses offered in their respective locales. Implications
for social change may include a better understanding of why these differences exist in an attempt
to further equal the opportunities for students across all locales. Please see Figures 1-4 for
further clarification and visual displays of the data.
TESTING FOR ONE-WAY ANOVA
4
TESTING FOR ONE-WAY ANOVA
5
References
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th
ed.). Thousand Oaks, CA: Sage Publications.
High School Longitudinal Study 2009 Dataset. (2009). (dataset file)
Laureate Education (Producer). (2016h). One-way ANOVA demonstration [Video file].
Baltimore, MD: Author.
Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science
statistics (6th ed.). Thousand Oaks, CA: Sage Publications.
…
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