Instructions: Review this document in its entirety! You are asked to interpret the data and write a report of your findings and inferences. You are also testing the hypotheses and you will determine whether or not to reject the null-hypotheses. Based on that determination, you will make a recommendation to your COO. Background: You are the Human Resources Manager of a company that cares greatly about its employee development program, especially pertaining to the millennial generation. You are aware of a study that compared traditional mentoring practices to reverse mentoring practices and you want to make a recommendation to the Chief Operating Officer about implementing a reverse mentoring program. Turnover is high, and you think that reverse mentoring may increase affective commitment and employees will stay in the organization. Reverse mentoring refers to tenured and older employees being mentored by new, younger employees. Traditional mentoring is the practice of an older, tenured worker mentoring a new employee. Your company already participates in a traditional mentoring program. You only have parts of the study and the interpretation of the data is missing. The question the study answered is as follows: Q1. Among employees of the millennial generation who participated in a mentoring program, to what extent, if any, does affective commitment to the organization differ based on participation in reverse vs. traditional mentoring, while controlling for quality and length and frequency of mentoring relationship. Hypotheses H10. There is no significant difference in affective commitment to the organization between Millennials participating in reverse mentoring compared to Millennials participating in traditional mentoring, controlling for quality and length and frequency of mentoring relationship. H1a. There is a significant difference in affective commitment to the organization between Millennials participating in reverse mentoring compared to Millennials participating in traditional mentoring, controlling for quality and length and frequency of mentoring relationship. Descriptive Statistics Table 3 Demographic Survey Age Answer Response % 1 18 - 23 10 11 2 24 - 29 41 46 3 30 - 34 39 43 Note: N = 90 Table 4 Demographic Survey Gender Answer Response % 1 Male 39 43 2 Female 51 57 Note: N = 90 Table 5 Demographic Survey Length of Employment Answer Response % 1 Less than 1 year 6 7% 2 1 year but less than 2 years 24 27% 3 2 years or more 60 67% Note: N = 90 Table 6 Demographic Survey Level of Education Answer Response % 1 Doctoral Degree 4 4% 2 Master Degree 15 17% 3 Bachelor Degree 35 39% 4 Associates Degree 18 20% 5 High School 18 20% 6 Did not graduate High School 0 0% Note: N = 90 LMX-7 Scores Calculation and Interpretation DATA: Based on the responses of each participant the LMX-7 score was calculated by totaling the responses to the 7 questions. On a Likert-type scale, points where assigned to each answer ranking from 1 to ...

1. Instructions:
Review this document in its entirety! You are asked to interpret
the data and write a report of your findings and inferences. You
are also testing the hypotheses and you will determine whether
or not to reject the null-hypotheses. Based on that
determination, you will make a recommendation to your COO.
Background: You are the Human Resources Manager of a
company that cares greatly about its employee development
program, especially pertaining to the millennial generation. You
are aware of a study that compared traditional mentoring
practices to reverse mentoring practices and you want to make a
recommendation to the Chief Operating Officer about
implementing a reverse mentoring program. Turnover is high,
and you think that reverse mentoring may increase affective
commitment and employees will stay in the organization.
Reverse mentoring refers to tenured and older employees being
mentored by new, younger employees. Traditional mentoring is
the practice of an older, tenured worker mentoring a new
employee. Your company already participates in a traditional
mentoring program.
You only have parts of the study and the interpretation of the
data is missing. The question the study answered is as follows:
Q1. Among employees of the millennial generation who
participated in a mentoring program, to what extent, if any, does
affective commitment to the organization differ based on
participation in reverse vs. traditional mentoring, while
controlling for quality and length and frequency of mentoring
relationship.
Hypotheses
H10. There is no significant difference in affective
commitment to the organization between Millennials
participating in reverse mentoring compared to Millennials
participating in traditional mentoring, controlling for quality
and length and frequency of mentoring relationship.

2. H1a. There is a significant difference in affective commitment
to the organization between Millennials participating in reverse
mentoring compared to Millennials participating in traditional
mentoring, controlling for quality and length and frequency of
mentoring relationship.
Descriptive Statistics
Table 3
Demographic Survey Age
Answer
Response
%
1
18 - 23
10
11
2
24 - 29
41
46
3
30 - 34
39
43
Note: N = 90
Table 4
Demographic Survey Gender
Answer
Response
%
1
Male
39
43
2

3. Female
51
57
Note: N = 90
Table 5
Demographic Survey Length of Employment
Answer
Response
%
1
Less than 1 year
6
7%
2
1 year but less than 2 years
24
27%
3
2 years or more
60
67%
Note: N = 90
Table 6
Demographic Survey Level of Education
Answer
Response
%
1
Doctoral Degree
4
4%
2
Master Degree
15

4. 17%
3
Bachelor Degree
35
39%
4
Associates Degree
18
20%
5
High School
18
20%
6
Did not graduate High School
0
0%
Note: N = 90
LMX-7 Scores Calculation and Interpretation
DATA:
Based on the responses of each participant the LMX-7 score was
calculated by totaling the responses to the 7 questions. On a
Likert-type scale, points where assigned to each answer ranking
from 1 to 6. The following guidelines established by Graen and
Uhl-Bien (1995) were used to interpret the meaning of the
scores: very high = 30–35, high = 25–29, moderate = 20–24,
low = 15–19, and very low = 7-14. Scores in the upper ranges
indicate stronger, higher-quality exchanges, whereas scores in
the lower ranges indicate exchanges of lesser quality.
Table 7
LMX-7 Scores (groups combined)
Answer
Response
%
1

5. Score of 30-35 - very high
39
43%
2
Score of 25-29 - high
36
40%
3
Score of 20-24 - moderate
12
13%
4
Score of 15-19 - low
3
3%
5
Score of 7-14 - very low
0
0%
Note: N = 90
Table 8
LMX-7 Scores (Traditional Mentoring Group)
Answer
Response
%
1
Score of 30-35 - very high
18
40%

6. 2
Score of 25-29 - high
20
44%
3
Score of 20-24 - moderate
5
11%
4
Score of 15-19 - low
2
4%
5
Score of 7-14 - very low
0
0%

7. Note: N = 45
Table 9
LMX-7 Scores (Reverse Mentoring Group)
Answer
Response
%
1
Score of 30-35 - very high
21
47%
2
Score of 25-29 - high
16
36%
3
Score of 20-24 - moderate
7
16%
4
Score of 15-19 - low
1
2%
5
Score of 7-14 - very low
0
0%
Note: N = 45
Length and Frequency of Mentoring
Length and frequency of mentoring was measured by
asking participants to select 1 of 4 options. The options were as

8. follows: a) less than six months, b) at least six months with a
minimum of two interactions, c) six months to one year with at
least four interactions, d) one year or more with five or more
interactions. For analyses purposes the string answers were
converted to numerical values with 1 representing less than 6
months, 2 represented at least six months with a minimum of
two interactions, 3 represented six months to one year with at
least four interactions, and 4 represented one year or more with
five or more interactions.
Table 10
Length and Frequency of Mentoring (groups combined)
Answer
Response
%
1
less than 6 months
10
11%
2
at least 6 months with a minimum of 1 interaction
21
23%
3
six months to one year with at least four interactions
31
35%
4
one year or more with five or more interactions
28
31%
Note: N = 90
Table 11
Length and Frequency of Mentoring (Traditional Mentoring
Group)

9. Answer
Response
%
1
less than 6 months
5
11%
2
at least 6 months with a minimum of 1 interaction
10
22%
3
six months to one year with at least four interactions
17
38%
4
one year or more with five or more interactions
13
29%
Note: N = 45
Table 12
Length and Frequency of Mentoring (Reverse Mentoring Group)
Answer
Response
%
1
less than 6 months
5
11%
2
at least 6 months with a minimum of 1 interaction
11
25%
3

10. six months to one year with at least four interactions
14
31%
4
one year or more with five or more interactions
15
33%
Note: N = 45
Affective Commitment Scores
Based on participant responses ranging from strong
agreement to strong disagreement to eight questions from the
Meyer and Allen (1991) Affective Commitment Survey, totals
were calculated for each response with the highest possible
score being 48 and the lowest possible score being 8. Four
items in the commitment scale were worded such that strong
agreement actually reflected a lower level of commitment and
were designed this way to encourage participants to think about
each statement carefully rather than agreeing or disagreeing
with statements in a pattern. These four items were thus
calculated in reverse key. The higher the score, the greater the
affective commitment to the organization (Meyer & Allen,
1991).
Table 13
Affective Commitment Scores (groups combined)
Answer
Response
%
1
40-48 very high level of commitment
34
38%
2
31-39 high level of commitment
30
33%

11. 3
21-30 moderate to low level of commitment
25
28%
4
20 < very low level of commitment
1
1%
Note: N = 90
Table 14
Affective Commitment Scores (Traditional Mentoring Group)
Answer
Response
%
1
40-48 very high level of commitment
14
31%
2
31-39 high level of commitment
15
33%
3
21-30 moderate to low level of commitment
16
36%
4
20 < very low level of commitment
0
0%
Note: N = 45
Table 15
Affective Commitment Scores (Reverse Mentoring Group)

12. Answer
Response
%
1
40-48 very high level of commitment
20
44%
2
31-39 high level of commitment
15
33%
3
21-30 moderate to low level of commitment
9
20%
4
20 < very low level of commitment
1
2%
Note: N = 45
Analysis of Covariance (ANCOVA)
A one-way ANCOVA was used to compare the traditional
mentoring group to the reverse mentoring group to determine
whether the different types of mentoring showed significant
differences on affective commitment to the organization.
Leader-member exchange quality (LMX) and length and
frequency of mentoring (LFM) were used as covariates to
determine if LMX and LFM would influence outcomes.
Figure 2 Linearity between LMX/LFM/Affective Commitment
Table 16

13. Homogeneity of Regression Slopes
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Corrected Model
977.187
5
195.437
4.796
.001
Intercept
469.941
1
469.941
11.531
.001
Mentoring Group
17.308
1
17.308
.425
.516
LFM
112.871
1
112.871
2.770
.100
LMX
814.048
1
814.048
19.975

14. .000
Mentoring Group * LFM
133.113
1
133.113
3.266
.074
Mentoring Group * LMX
2.708
1
2.708
.066
.797
Error
3423.313
84
40.754
Total
119963.000
90
Corrected Total
4400.500
89
Table 17
Shapiro-Wilk’s Tests of Normality

15. Kolmogorow-Smirnova
Shapiro-Wilk
Type of mentoring
Statistic
df
Sig.
Statistic
df
Sig.
Standardized Residual for
Traditional
.079
45
.200*
.983
45
.727
Affective Commitment
Reverse
.093
45
.200*
.972
45
.336
Note: *This is lower bound of the true significance a. Lilliefors
Significance Correction
There was homogeneity of variances, as assessed by Levene’s
test of homogeneity of variance (p = .868).

16. Figure 3 Homoscedasticity
Table 18
Levene’s Test of Equality of Error Variances
Dependent Variable: Affective Commitment
F
df1
df2
Sig.
.028
1
88
.868
Table 19
Mean and Standard Deviation
Type of Mentoring
Mean
Std. Deviation
N
Traditional
35.02
6.861
45
Reverse
36.64
7.183
45
Total
35.83
7.032
90
Table 20

17. Adjusted Means
95% Confidence Interval
Group
Mean
Std. Error
Lower Bound
Upper Bound
Traditional
34.984a
.959
33.078
36.890
Reverse
36.683 a
.959
34.776
38.589
Note: a = covariates appearing in the model are evaluated at the
following values: LMX = 28.63, LFM = 2.86.
Table 21
Test of Between-Subjects Effects
Dependent Variable: Affective Commitment
Source
Type III Sum of Squares
df
Mean Square
F
Sig.
Partial Eta Squared
Corrected Model
842.173
3

18. 280.724
6.785
.000
.191
Intercept
523.554
1
523.554
12.654
.001
.128
LMX
768.103
1
768.103
18.564
.000
.178
LMF
114.683
1
114.683
2.772
.100
.031
Mentoring Group
64.919
1
64.919
1.569
.214
.018
Error
3558.327
86
41.376

19. Total
119963.000
90
Corrected Total
4400.500
89
To further evaluate the differences between reverse and
traditional mentoring and affective commitment to the
organization, two sub-groups were extracted from the overall
data. The sub-groups were divided into the participants that had
a very high or high affective commitment score and the
participants who had a moderate to low or very low affective
commitment score.
Table 22
Means of Affective Commitment (high/low), LMF, LMX
Traditional Low Affective Commitment
Reverse
Low
Affective Commitment
Traditional High Affective Commitment

20. Reverse High Affective Commitment
LFM
2.77
3.08
2.95
2.64
LMX
27.19
27.7
30.68
29.55
Affective Commitment
30.08
30.78
41.79
42.77
Note: N = 90; 41 High Affective Commitment (22 Reverse, 19
Traditional); 49 Low Affective Commitment (23 Reverse, 26
Traditional)
Table 23
Means of Affective Commitment, LMF, LMX by Age Group
Age Group
LFM
LMX
Affective Commitment

21. 18-23
2.50
27.30
34.40
24-29
2.83
28.66
35.17
30-34
2.97
28.95
36.90
Note: N = 90
Proper In-Text Citations and References
By Bruce Heiman and Linda Lam
-13
SFSU
CITATIONS-how to cite information within the main body of
text
One author:
Hall (2003) indicates similar patterns for investing occur.
US firms account for most of the FDI in the world economy
(Hall, 2003).

22. Three or more authors-one article:
Holland, Holt, Levi, and Beckett (1983) indicate that…
OR (after the first citation)
Holland et al. (1983) also found that….
Several articles, single + multi-authors:
After the Civil Rights movement a growing number of
racial/ethnic scholars such
as Almaguer (1975), Barrera (1978), and Takaki (1979)
found,…
• The subject of this study seemed to perform their duties as
determined by the institutional arrangements within which they
worked (Watson,
Kumar, & Michaelsen, 1993; Cox, Lobel, & McLoed, 1991;
Fitzgerald, 1993).
(Note: semicolons [;] separate different sources inside one
citation)
Exact Quotation of Sources:
Charles W. Hall (2003) offers some interesting causes and
reflections about
“crucial-to-measure-the-impact-of import quotas and voluntary
export restraints”
(p.176).
He stated, “An import quota is a direct restriction on the
quantity of some good
that may be imported into another country” (Hall, 2003, p.176).

23. Citing two or more works by the same author in one in-text cite:
According to Charles W. Hall (1994; 2003), “low-cost
transportation has made it
more economical to ship products around the world.”
REFERENCES (end of document bibliography)
Rule: If you cite it, you must put the detailed bibliographical
information on the source in
the References section.
Rule: If you put it into the References section, you MUST have
cited it in the main text or
a footnote.
Sometimes you have to improvise: the goal of ALL references is
to offer information that
allows the reader to easily find the full content of your source.
This is a rather simple “author-date” format. Use any format
(MLA or APA or other) but
apply consistently.
Book, 1 author:
Arrow, K. J. (1974). The limits of organization. New York,

24. Norton & Co.
Book, 2 authors:
Cooper, W. E. and Emory, L. (1995). Business research
methods. Chicago: Irwin.
Journal, 1 author:
Conner, K. R. (1991). “A historical comparison of resource-
based theory and five
schools of thought within industrial organization economics: Do
we have a new
theory of the firm?” Journal of Management 17 (1): 121-154.
*Note on above example: 17 (1): 121-154. is the formatted way
to indicate where
one’s journal is from. In other words, it reads out to mean
Volume 17, first
issue/issue 1, pages 121-154.
Journal, 2 authors:
Conner K. R. and C. K. Prahalad (1996). “A resource-based
theory of the firm:
Knowledge versus opportunism.” Organization Science 7(5):
477-501.
*Note on indenting—you could and should format all multi-line
references as
follows:
Conner K. R. and C. K. Prahalad (1996). “A resource-based
theory of the firm:

25. Knowledge versus opportunism.” Organization Science 7(5):
477-501.
[This aids in readability of the first author’s name]
_____________________________________________________
__________________
*References for magazine and newspaper articles can be placed
in a footnote or at an
end of the essay, in References, but not both.
Magazine Article:
Corliss, R. (1993, September 13). “Pacific overtures.” Time,
142, 68-70.
Newspaper Article:
“For job seekers, a toll free gift of expert advice.” (1993,
December 12) New
York Times, p. D1.
Examples of References for Internet-based Sources
[Try to stay focused on the Author(s), even if it is aninstitution,
firm, or website, though
tht last is not most-preferred, as it may not be a permanent
address—permanent web-links
are preferred].
Individual works:

26. Pi, M. (No date). “Psychology with style.” [Online]. Available:
http://www.uwsp.edu/acad/psych/apa4.htm [1998, July 7]
Journals:
Malmstrom, V. H. (1995, Jan.). “Geographical origins of the
Tarascans.”
Geographical Review [Online], 85, 31 (10 pages). Available:
CALIFORNIA
DIGITAL LIBRARY (CDL)® (MAGS). [1997, August 10].
*When citing a printout of the text in your document instead of
the original journal
article use [n.p.] (no pagination) since no page numbers exist.
Full-text internet articles:
Carranza, L.E. (1994). “Le Corbusier and the problems of
representation.” Journal
of Architectural Education [Online], 48(2). Available:
http://www.mitpress.mit.edu/jrnls-catalog/File:jae48-2.html.
[1997, September
22].
Newspapers:
Ferriss, S. (1995, July 16). “Latino rock - hot like a ‘volcano’:
Mission District
label 1st to focus on trend.” San Francisco Examiner [Online],
p. C1. Available:
http://www.examiner.com. [1997, September 23].

27. Encyclopedias (e.g., wikis, others):
“Bosnia and Herzegovina.” (1997). In Britannica Online
[Online]. Available:
http://www.eb.com: 180/cgi-bin/g?DocF=micro/79/88.html.
[1997, September
23].
IBUS 593 Essay Grading Rubric:
1. Writingmust have correct grammar and usage. (Max
grade=8 if grammar/usage/styleis very
weak)
2. There should be no spelling mistakes. (-1)
3. All parts of the problem statement must be
addressed. (-1 or -2)
4. Must describe and solve the problem clearly
5. Adhere to Page length, Word count, Format
requirements. (-1)
6. Clear introduction and conclusion. (-1/2)
7. Clarity in the arguments. (-1 to -4)
8. Convincing argumentsto support the stance. (-2 to
-5)

28. 9. References must be correctly cited. (-1 to -2)
10. Most important: Is your solution convincing to
the reader?
I use this rubric for grading all written
submissions. Work to the rubric, and your
grades should be fine.
Now you know what I look for!