jad12286-sup-0001-revisions_1_joa_summplementary_material_clean_final
docx
keyboard_arrow_up
School
University of Texas *
*We aren’t endorsed by this school
Course
303
Subject
Statistics
Date
Feb 20, 2024
Type
docx
Pages
45
Uploaded by PresidentKnowledge4748
SMU and offline Need-based Experiences
Supplementary Material
Supplementary Material
Table of Content
1.
Need-based experiences during social media use and off-line activities
1.1. Background information
1.2. Instructions and items 1.3. Psychometric Information
2.
Vitality Items
3.
Additional descriptive information
4.
Additional analyses high and low social media use
5.
Additional analyses on each basic psychological need separately 6.
Figures response surface analyses
6.1. Need Satisfaction
6.2. Need frustration
1
SMU and offline Need-based Experiences
Supplementary Material
1.
Need-based experiences during social media use and off-line activities
1.1. Background information
Purpose. The purpose of the adjusted scale is to measure the Basic Psychological Needs
(Vansteenkiste et al., 2020, 2023) separately in the domain of social media, and to compare
this with need experiences in offline activities. For this purpose, the same set of items is
repeated in the two domains separately. To avoid repetitiveness, the items for the offline
domain were presented somewhat later in the questionnaire.
Construction of the Scale. The present scale is an adjusted version of the 12-item version
of the BPNSFS (Chen et al., 2015; Van Der Kaap-Deeder et al., 2021). The wording of the
items were simplified or adjusted to (1) ensure validity in the domain of social media, (2)
keep the items 'domain-neutral' (i.e., the wording does not lean more towards one domain or
the other) so that an equivalent comparison can be made between need experiences in the two
domains, (3) to be age-appropriate for adolescents. Specific adjustments for each item: ⎯
For item 1, "in the things I undertook" was replaced by "in what I did”. This simpler
wording fits better with the social media domain. ⎯
For item 2, 'disappointed in my accomplishments' was replaced with 'disappointed in
my skills' because accomplishments in the social media domain might be ambiguous.
⎯
For item 3, 'cold and distant' was replaced with 'unfriendly' to avoid confusion with
physical proximity, which by definition is not part of the social media domain.
⎯
For item 8 'excluded' was replaced with 'rejected' because excluded in the social media
domain can be understood as not being added in a group chat or page while the
connotation of excluded in everyday life extends further. ⎯
For item 6, replace 'my decisions reflect what I really want' with 'did I feel like I could
really be myself'. This item is in line with autonomy satisfaction in the scale of
Reinecke et al., 2014. This adjustment was deemed necessary because autonomy in the
domain of social media seems to be broader than making choices and essentially
seems to be about being able to express oneself freely and authentically. ⎯
For item 9, 'felt compelled to' was replaced with 'experienced pressure to '. This was
changed because spending time on social media is, by definition, a freely chosen
activity. In contrast, autonomy frustration in the social media domain seems to be
more about experiencing 'pressure' (e.g., peer pressure, pressure to post, pressure to be
online). ⎯
For item 11, "with whom I spent time" was replaced by "with whom I interacted,"
since spending time refers more to physical presence, which by definition is lacking in
the social media domain.
2
SMU and offline Need-based Experiences
Supplementary Material
1.2. Instructions and items Instructions. In the following items we are interested in what you feel and how you think
when you spent time on social media.
In the past month, when I used social media… 1
2
3
4
5
Not at all true
Completely true
1.
I felt a sense of freedom in what I did.
1
2
3
4
5
2.
I felt disappointed in what I can. 1
2
3
4
5
3.
I felt that people who are important to me were unkind to me.
1
2
3
4
5
4.
I did most of the things because I had to.
1
2
3
4
5
5.
I felt confident that I could do things well.
1
2
3
4
5
6.
I felt that I could be fully myself.
1
2
3
4
5
7.
I felt connected with people who I care for.
1
2
3
4
5
8.
I felt rejected from the group I want to belong to.
1
2
3
4
5
9.
I felt pressure to do things contrary to my liking.
1
2
3
4
5
10.
I felt competent in what I was doing.
1
2
3
4
5
11.
I had warm feelings towards the people I had contact with
1
2
3
4
5
12.
I felt insecure about what I am able to do.
1
2
3
4
5
A few minutes ago we asked you about your thoughts and feeling when you spend time on
social media. With the following questions, we would like to know how you feel and what
you think when you do NOT use social media. Think about your other activities like school,
with your friends or with your family, … We will summarize this with the term being
“offline”. In the past month, when I was offline… 1
2
3
4
5
Not at all true
Completely true
13.
I felt a sense of freedom in what I did.
1
2
3
4
5
14. I felt disappointed in what I can. 1
2
3
4
5
15.
I felt that people who are important to me were unkind to me.
1
2
3
4
5
16. I did most of the things I did because I had to.
1
2
3
4
5
3
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
17. I felt confident that I could do things well.
1
2
3
4
5
18. I felt that I could be fully myself.
1
2
3
4
5
19. I felt connected with people who I care for.
1
2
3
4
5
20. I felt rejected from the group I want to belong to.
1
2
3
4
5
21.
I felt pressure to do things contrary to my liking.
1
2
3
4
5
22.
I felt competent in what I was doing.
1
2
3
4
5
23.
I had warm feelings towards the people I had contact with
1
2
3
4
5
24.
I felt insecure about what I am able to do.
1
2
3
4
5
Scoring information:
SMU autonomy satisfaction: items 1, 6
SMU autonomy frustration: items 4, 9
SMU relatedness satisfaction: items 7, 11
SMU relatedness frustration: items 3, 8 SMU competence satisfaction: items 5, 10
SMU competence frustration: items 2, 12
offline autonomy satisfaction: items 13, 18
offline autonomy frustration: items 16, 21
offline relatedness satisfaction: items 19, 23
offline relatedness frustration: items 15, 20
offline competence satisfaction: items 17, 22
offline competence frustration: items 14, 24
Note: The full-item version was adopted in Sample 2 and 3 of this manuscript. Items in bold
were used in Sample 1. 1.3. Psychometric Information
4
SMU and offline Need-based Experiences
Supplementary Material
1.3.1.
Sample 1
A.
Reliability analyses Table S1. Reliability analysis on items measuring offline need-based experiences
Offline Need-Based Experiences
SMU Need-Based Experiences
Item
Cronb
ach’s
Alpha
Alpha
if item
deleted
Inter-item
correlations
Cronb
ach’s
Alpha
Alpha
if item
deleted
Inter-item
correlations
1.
2.
3.
1.
2.
3.
1. Autonomy sat
.71
.54
-
.60
.52
-
2. Relatedness sat
.71
.69
.45
-
.60
.55
.28
-
3. Competence sat .71
.61
.53
.37
-
.60
.44
.38
.36
-
1.
2.
3.
1.
2.
3.
1. Autonomy frus
.62
.56
-
.61
.48
-
2. Relatedness frus
.62
.53
.29
-
.61
.53
.37
-
3. Competence frus
.62
.45
.37
.40
-
.61
.54
.37
.32
-
5
SMU and offline Need-based Experiences
Supplementary Material
B.
Factor Analyses
Table S2.
Exploratory Factor analysis on items measuring need-based experiences offline and during
SMU
Offline need-based
experiences
SMU need-based
experiences
Rotated Component Matrix
Eigenvalues
above 1
2 Factors
Eigenvalues above 1
Component
Component
Component
1
1
2
1
2
1. Autonomy satisfaction
.78
-.44
.67
.82
2. Relatedness satisfaction
.61
.89
.78
3. Competence satisfaction .71
-.40
.61
.87
4. Autonomy frustration
-.64
.79
.80
5. Relatedness frustration
-.66
.51
-.42
.82
6. Competence frustration -.66
.78
.77
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 3 iterations.
C. Conclusions
The 2 x 6-item version to measure basic psychological need experiences in both domains
resulted in fairly low Cronbach’s Alpha’s. Factor and item analyses yielded no indications for
bad items. Therefore, the low reliability scores are likely due to the limited number of items
being used. Hence, in sample 2 and 3, a 2 x 12-item version was adopted. The factor structure for the SMU-domain more clearly distinguished between satisfaction and
frustration items compared to the offline-domain. Still, confirmatory factor analyses with 2
factors indicated satisfaction-items yielded the highest factor loadings with the factor ‘offline
satisfaction’, and that frustration-items yielded the strongest factor loadings with the factor
‘offline frustration’.
6
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
1.3.2.
Sample 2
A.
Reliability analyses
Table S3. Reliability analysis on items measuring offline need-based experiences and SMU experiences.
Offline Need-Based Experiences
SMU Need-Based Experiences
Item
α
if
item
dele
ted
Inter-item correlations
α
if item
dele
ted
Inter-item correlations
α
= .
80
1.
2.
3.
4.
5.
6.
α
=
.74
1.
2.
3.
4.
5.
6.
1. Aut sat_1
.79
-
.71
-
2. Aut sat_2
.74
.46
-
.69
.48
-
3. Rel sat_1 .77
.35
.50
-
.71
.23
.33
-
4. Rel sat_2
.77
.36
.56
.56
-
.70
.27
.30
.49
-
5. Comp sat_1
.79
.33
.40
.30
.27
-
.70
.23
.36
.32
.39
-
6. Comp sat_2
.77
.32
.46
.33
.38
.53
-
.72
.30
.32
.20
.29
.35
-
α
=
.79
1.
2.
3.
4.
5.
6.
α
=
.75
1.
2.
3.
4.
5.
6.
1. Aut frus_1
.78
-
.73
-
2. Aut frus_2
.76
.54
-
.69
.54
-
3. Rel frus_1 .75
.30
.42
-
.71
.24
.33
-
4. Rel frus_2
.76
.27
.36
.57
-
.71
.22
.36
.51
-
5. Comp frus_1
.76
.34
.35
.42
.40
-
.72
.19
.30
.24
.28
-
6. Comp frus_2
.77
.28
.31
.42
.40
.55
-
.70
.26
.33
.32
.31
.54
-
7
SMU and offline Need-based Experiences
Supplementary Material
B.
Factor Analyses
Table S4.
Exploratory Factor analysis on items measuring need-based experiences offline and during
SMU
Offline Need-Based
Experiences
SMU Need-Based Experiences
Rotated Component Matrix
Eigenvalues above 1
2 factors
(fixed)
Eigenvalues
above 1
2 factors
(fixed)
Component
Compone
nt
Component
1
2
3
1
2
1
2
3
1
2
1. Aut sat_1
.58
.58
.62
.49
2. Aut sat_2
.69
.74
.68
-.40
.62
3. Rel sat_1 .81
.61
.36
.6
7
,65
4. Rel sat_2
.82
.62
.40
.6
6
.69
5. Comp sat_1
.80
.79
.65
.73
6. Comp sat_2
.42
.59
.74
.69
.61
7. Aut frus_1
.7
3
.67
.75
.70
8. Aut frus_2
.8
2
.78
.78
.77
9. Rel frus_1 .6
7
.6
8
.52
-.5
9
.63
10. Rel frus_2
.5
5
.6
1
.48
-.6
7
.62
11. Comp frus_1
.4
4
-.68
.69
-.44
.50
.54
12. Comp frus_2
.3
7
-.72
-.36
.59
-.48
.54
.60
-.38
8
SMU and offline Need-based Experiences
Supplementary Material
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization.
Rotation converged in 15 iterations.
1.3.3.
Sample 3
A.
Reliability analyses Table S5. Reliability analysis on items measuring offline need-based experiences
Offline Need-Based Experiences
SMU Need-Based Experiences
Item
α
if
item
dele
ted
Inter-item correlations
α
if item
dele
ted
Inter-item correlations
α
= .
86
1.
2.
3.
4.
5.
6.
α
=
.86
1.
2.
3.
4.
5.
6.
1. Aut sat_1
.85
-
.82
-
2. Aut sat_2
.83
.51
-
.79
.43
-
3. Rel sat_1 .83
.43
.56
-
.80
.35
.47
-
4. Rel sat_2
.83
.45
.53
.71
-
.80
.36
.42
.65
-
5. Comp sat_1
.83
.45
.53
.45
.43
-
.80
.41
.46
.38
.37
-
6. Comp sat_2
.84
.43
.50
.44
.44
.69
-
.79
.40
.49
.46
.44
.62
-
9
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
α
=
.84
1.
2.
3.
4.
5.
6.
α
=
.84
1.
2.
3.
4.
5.
6.
1. Aut frus_1
.81
-
.78
-
2. Aut frus_2
.81
.61
-
.79
.52
-
3. Rel frus_1 .83
.43
.40
-
.80
.43
.35
-
4. Rel frus_2
.83
.37
.44
.54
-
.81
.45
.45
.62
-
5. Comp frus_1
.81
.54
.45
.38
.38
-
.79
.49
.41
.33
.36
-
6. Comp frus_2
.81
.51
.48
.37
.42
.68
-
.79
.43
.53
.37
.44
.49
-
B.
Factor Analyses
Table S6.
Exploratory Factor analysis on items measuring offline need-based experiences (based on
Eigenvalues above 1)
Offline Need-Based Experiences
SMU Need-Based
Experiences
Rotated Component Matrix
Eigenvalues above 1
2 factors
(fixed)
Eigenvalues above 1
Component
Component
Component
1
2
3
1
2
1
2
1. Aut sat_1
.65
.66
.64
2. Aut sat_2
.73
.75
.73
3. Rel sat_1 .79
.80
.76
4. Rel sat_2
.78
-.37
.79
.73
5. Comp sat_1
.71
-.4
8
.72
.74
6. Comp sat_2
.71
-.4
4
.72
.79
7. Aut frus_1
.6
3
.46
.78
.76
10
SMU and offline Need-based Experiences
Supplementary Material
8. Aut frus_2
.5
3
.54
.74
.75
9. Rel frus_1 .76
.63
.70
10. Rel frus_2
.74
.63
.74
11. Comp frus_1
.8
0
.76
.67
12. Comp frus_2
.8
0
.77
.74
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization.
Rotation converged in 15 iterations.
2.
Vitality Items
As mentioned in the manuscript, the items tapping into vitality slightly differed in each
sample. Below the English version of those items can be found. Sample 1
Sample 2
Sample 3
At the moment I feel alive and dynamic
Lately I have been feeling alive
At the moment I feel alive These days I am bursting with life and energy
I feel so alive I might even be bursting with energy
Op dit ogenblik heb ik veel positieve energie en zin voor
initiatief
I feel powerful right now
Over the last few weeks, I have had a lot of energy and creativity
I feel powerful and vital right now
11
SMU and offline Need-based Experiences
Supplementary Material
3.
Additional descriptive information
Table S7
Means, Standard Deviation and Observed Range for Need Composite and Need Specific
Scores across Samples
Sample
1
2
3
Mean
SD
Range
Mean
SD
Range
Mean
SD
Range
Offline satisfaction
3.84
.75
1-5
3.86
.57
1.5-5
3.57
.75
1-5
Autonomy
3.68
1.01
1-5
3.83
.76
1.5-5
3.61
.86
1-5
Competence
3.81
.89
1-5
3.66
.67
1.5-5
3.26
.90
1-5
12
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Relatedness
4.04
.89
1-5
4.20
.66
1.5-5
3.83
.87
1-5
SMU satisfaction
3.57
.77
1-5
3.80
.56
2-5
3.05
.80
1-5
Autonomy
3.73
1.05
1-5
3.81
.81
1.5-5
3.18
.93
1-5
Competence
3.63
.946
1-5
3.63
.66
2-5
2.82
.93
1-5
Relatedness
3.44
1.09
1-5
3.97
.70
2-5
3.16
1.00
1-5
Offline frustration
2.33
.87
1-5
2.34
.66
1-5
2.32
.82
1-5
Autonomy
2.30
1.12
1-5
2.77
.87
1-5
2.36
1.03
1-5
Competence
2.67
1.26
1-5
2.34
.81
1-5
2.64
1.02
1-5
Relatedness
2.01
1.08
1-5
1.91
.80
1-5
1.96
.89
1-5
SMU f
rustration
1.99
.77
1-4.33
2.13
.68
1-5
2.04
.77
1-5
Autonomy
1.70
.93
1-5
2.27
.93
1-5
1.83
.87
1-5
Competence
2.45
1.17
1-5
2.18
.88
1-5
2.48
1.03
1-5
Relatedness
1.83
.96
1-5
1.94
.89
1-5
1.83
.85
1-5
In Sample 1, the mean difference between SMU and offline of -0.27 for need satisfaction
(
F
(1,370) = 13740.87, p < .001, η
2 = .068) and -0.34 for need frustration (
F
(1,370) = 3457.37,
p
< .001, η
2 = .160) were both statistically significant. In Sample 2, the mean difference in SMU and offline was significant for need frustration
(-.21, F
(1,178) = -11332.46, p
< 0.001, η
2 = .010), and for need satisfaction (-.06, t
(1,178) =
19.95, p
< 0.001, η
2 = .101). In Sample 3, the mean differences in SMU and offline were significant for both need
satisfaction (.47, F
(1,4776) = 138177.72, p < .001, η
2 = .240) and need frustration (.28,
F
(1,4708) = 709.51, p < .001, η
2 = .087).
Table S8
Occurrence of Domain-(In)congruence in Need Satisfaction and Frustration Across Samples
Need Satisfaction
Need Frustration
Sample 1: offline < SMU: 17.25%
offline < SMU: 10.51%
offline = SMU: 47.98%
offline = SMU: 53.10%
offline > SMU: 34.77%
offline > SMU: 36.39%
Sample 2:
13
SMU and offline Need-based Experiences
Supplementary Material
offline < SMU: 26.40%
offline < SMU: 19.32%
offline = SMU: 42.70%
offline = SMU: 32.39%
offline > SMU: 30.90%
offline > SMU: 48.30%
Sample 3: offline < SMU: 10.03%
offline < SMU: 12.94%
offline = SMU: 39.95%
offline = SMU: 49.77%
offline > SMU: 50.01%
offline > SMU: 37.29%
Note.
Incongruence was determined by scores in the SMU domain being half a standard
deviation above or below the offline domain, with scores falling within this range considered
as non-discrepant or equal (see also Shanock et al., 2010)
4.
Additional analyses high and low social media use
All samples were divided into two subsamples, high social media users and low social media
users. High users were those who used over 5 hours per day (
n
1 = 224, n
2 = 93, n
3 = 2845)
low users were those using less than 5 hours a day (
n
1 = 174, n
2 = 86, n
3 = 2097. Polynomial
14
SMU and offline Need-based Experiences
Supplementary Material
regression analyses were performed on those subsamples separately to see whether similar
patterns would occur. Results are presented in Table S9 (need satisfaction) and Table S10
(need frustration). Scores for the group of high users are in bold and italic. Overall, the
patterns of analyses were similar as of those in the main analyses. As for need satisfaction, some evidence was found in two cases that incongruency effects
where especially the offline domain is predictive of the mental health outcome were
somewhat less pronounced in the high users group (e.g., Sample 1, life satisfaction). In one
case, namely the effect on sleep quality in sample 2, the a3 effect showed that the SMU
domain was more important in predicting adolescents’ sleep quality. In 3 cases, the
incongruency effect as such (a4) was significant for the low users group, but not for the high
users group. As for need frustration, results were somewhat more mixed. Conclusion
: Both among high and average users of social media, the joint effects (a1) point in
the same direction, with need satisfaction in both domain having the most favorable effects,
while need frustration in both domains results in the least favorable effects in terms of
adolescents mental health. On top of that, some variation can be observed in the incongruity
(a3, a4) effects. 15
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Table S9
Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on Need Satisfaction in SMU and Offline Activities – high social media users separated from low users Vitality
Life Satisfaction
Sample
1
2
3
1
2
3
Polynomial regression coefficients
b1 offline
.55***
.50***
.24***
.32**
.49***
.55***
.42***
.48***
.18*
.32**
.55***
.61***
b2 SMU
.24**
.16
.17*
.20
.07**
-.02
.22**
.10
.12
.10
.07**
-.05
b3 offline
2
.05
-.02
-.17***
.08
.05**
.07***
.04
-.14*
-.10***
.09
.02
.05*
b4 offline x SMU
.12
-.02
-.04
.08
.06**
.09***
.04
.07
.05
.04
.07**
.09***
b5 SMU
2
-.12*
.05
.06
-.16**
-.01
-.04*
.01
.10*
.03
-.19***
-.01
-.04*
Response surface parameters
a1 slope LOC .79***
.66***
.41***
.52***
.57***
.53***
.64***
.58***
.30***
.42***
.62***
.56***
a2 curve LOC .06
.00
-.16**
-.01
.10***
-.12***
.08
.02
-.02
-.05
.07***
.11***
a3 slope LOIC .32*
.34*
.07
.12
.42***
.56***
.21
.38*
.06
.21
.47***
.66***
a4 curve LOIC -.19
.05
-.07
-.17
-.02
-.11
.01
-.11
-.11
-.14
-.06
-.08
16
SMU and offline Need-based Experiences
Supplementary Material
Sleep Quality
Anxiety
Depression
Sample 1
2
3
1
2
1
2
Polynomial regression coefficients
b1 offline
.10
.18*
-.13
.18*
.17***
.19***
-.26***
-.31***
-.04
-.12
-.28***
-.31***
-.08
-.21*
b2 SMU
.21*
.09
.20*
.18*
.02
-.02
-.17**
-.05
-.12
-.23**
-.17**
-.02
-.09
.02
b3 offline
2
-.03
-.11
-.08**
.05
.00
.02
.01
.06
.06***
.00
.01
.06
.04
.06
b4 offline x SMU
-.03
.18*
.02
-.17**
.03
.05**
-.04
-.03
-.06
-.03
-.05
-.05
-.00
-.17
b5 SMU
2
.04
-.08
.05
.11**
-.02
-.02*
-.00
-.06
-.02
.10*
.01
-.01
-.04
.19***
Response surface parameters
a1 slope LOC .31***
.27**
.07
.35***
.18***
.17***
-.44***
-.36***
-.16**
-.34***
-.44***
-.34***
-.17**
-.20**
a2 curve LOC -.02
-.02
-.01
-.01
.01
.05**
-.03
-.03
-.01
.07**
-.03
.01
-.00
.08
a3 slope LOIC -.11
.09
-.33*
.00
.15***
.20***
-.09
-.26**
.08
.11
-.11
-.29**
.02
-.23
a4 curve LOIC .04
-.37*
-.05
-.32**
-.01
-.05*
.04
.12
.11*
.13
.07
.11
.00
.42*
17
SMU and offline Need-based Experiences
Supplementary Material
Table S10
Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on Need Frustration in SMU and Offline Activities – high social media users separated from low users Vitality
Life Satisfaction
Sample
1
2
3
1
2
3
Polynomial regression coefficients
b1 offline
-.40***
-.29**
-.21
-.33*
-.37***
-.43***
-.24*
-.30**
-.36***
-.35***
-.48***
-.41***
b2 SMU
-.18
.07
-.10
-.06
-.05
.01
-.34***
-.04
.05
-.06
-.01
-.06
b3 offline
2
-.03
-.06
-.11
-.01
-.02
-.05*
-.01
-.00
-.08
.02
-.30***
-.10***
b4 offline x SMU
.20
.20*
.15
.18
.09**
.06*
.04
.08
.14
.01
-.19**
.09**
b5 SMU
2
.05
.04
-.01
-.05
-.05*
-.04
.14
.02
.04
.06
.01*
-.05
18
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Response surface parameters
a1 slope LOC -.58***
-.36***
-.30***
-.39**
-.42***
-.42***
-.58***
-.34***
-.30***
-.41***
-.48***
-.47***
a2 curve LOC .22**
.18*
.03
.12
.03
.03
.18*
.10
.09
-.09
-.01
.06**
a3 slope LOIC -.22
-.21
-.11
-.26
-.32***
-.45***
.10
-.26
-.41**
-.29***
-.30***
.36***
a4 curve LOIC -.18
-.22
-.27
-.24
-.16**
.15**
.10
-.06
.17
-.06
-.18***
.23***
Sleep Quality
Anxiety
Depression
Sample 1
2
3
1
2
1
2
Polynomial regression coefficients
b1 offline
-.03
.05
-.09
-.29**
-.10***
.19***
.22***
.20***
-.13
.16*
.28***
.10
.22***
.21*
b2 SMU
-.13
-.26**
-.04
.01
-.07**
-.00
.12
.06
-.14*
.17*
.15**
.16*
.07
.03
b3 offline
2
-.10
-.16**
.01
-.02
-.04*
-.01
.11
.03
.09
.05
.03
.10**
.05**
.11*
19
SMU and offline Need-based Experiences
Supplementary Material
b4 offline x SMU
.06
.30***
.04
.00
.02
.02
.07
.04
-.16
-.04
-.09
-.20**
.01
-.05
b5 SMU
2
-.03
-.17*
.07
.01
.01
-.03
-.17*
-.07
.03
-.05
.07
.07
.01
-.03
Response surface parameters
a1 slope LOC -.22**
-.21*
-.13
-.28**
-.16***
-.19***
.34***
.26***
-.27***
.33***
.43***
.27***
.29***
.24***
a2 curve LOC .06
-.02
.07
-.01
-.00
-.02
-.06
-.05
.05
-.05
.01
-.03
.07*
.03
a3 slope LOIC -.03
.31
-.04
-.31*
-.03
-.19***
.10
.14
-.01
-.01
.12
-.06
.15
.18
a4 curve LOIC .12
-.63***
-.02
-.02
-.05
-.08*
.28*
.12
.27
.04
.19
.37**
.04
.13
20
SMU and offline Need-based Experiences
Supplementary Material
5.
Additional analyses on each basic psychological need separately Although an aggregated score is used in the main analyses of our paper, assessing the needs
separately might provide a more nuanced understanding of the results. Therefore, the results
of polynomial regressions with response surface analyses on autonomy, competence and
relatedness in both domains are depicted in Table S11-16.
Conclusion
: Note that little systematic differences could be found throughout the three
samples, except that the supplementary effects were less systematic in case of the need for
relatedness, compared to autonomy and competence. This might suggest that relatedness is
more comparably throughout both domains. 21
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Table S11.
Sample 1: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need satisfaction.
Vitality
Life Satisfaction
Sleep Quality
Depression
Anxiety
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
.52***
.35***
.46***
.43***
.27***
.34***
.07
.10
.12*
-.24***
-.22***
-.24***
-.34***
-.26***
-.29***
b
2 SMU
.04
.21**
.14
.06
.07
.12
.13*
.09
.08
-.03
-.07
-.10*
-.03
-.04
-.09
b
3 offline
2
.05
.01
.05
.01
.05
-.04
-.07
-.02
-.02
.03
.00
.01
-.03
.04
.01
b
4 offline x SMU
.03
.02
.10
-.01
.09
.09
.05
.01
.02
-.03
-.04
-.07
.01
-.02
-.06
b
5 SMU
2
-.09
.01
-.03
-.06
-.02
.03
.03
-.01
-.04
.05
.00
-.07
.02
-.00
-.02
Response surface parameters
a
1 slope LOC
.56***
.57***
.59***
.48***
.34***
.46***
.20**
.18**
.20***
-.27***
-.28***
-.33***
-.37***
-.30***
-.38***
a
2 curve LOC
-.01
.05
.13*
-.07
.12
.09*
.01
-.02
-.05
.04
-.03
-.02
-.00
.02
-.07
a
3 slope LOIC
.48***
.14
.32**
.37***
.20
.23
-.05
.01
.04
-.21**
-.15*
-.14
-.31***
-.22**
-.20*
a
4 curve LOIC
-.07
.01
-.07
.07
-.06
-.09
-.10
-.04
-.08
.11*
.04
.10
-.03
.05
.05
R
2
.23***
.14***
.22***
.21***
.07***
.18***
.06***
.03*
.07***
.18***
.11***
.22***
.21***
.12***
.22***
Note. * p<.05, ** p<.01, ***p<.001
22
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Table S12.
Sample 1: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need frustration.
Vitality
Life Satisfaction
Sleep Quality
Depression
Anxiety
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
-.34***
-.36***
-.36***
-.20**
-.28***
-.28***
-.02
-.10
-.10
.15**
.19***
.19***
.18**
.15**
.15**
b
2 SMU
-.15
-.07
-.07
-.23**
-.18*
-.18*
-.10
.00
.00
.15**
.13**
.13**
.11*
.13*
.13*
b
3 offline
2
.03
.08
.08
-.02
.07
.07
-.04
.01
.01
.03
.00
.00
.02
.04
.04
b
4 offline x SMU
.15**
.14*
.14*
.15**
.11
.11
.14**
.06
.06
-.07
-.15**
-.15**
-.10*
-.08
-.08
b
5 SMU
2
-.04
.03
.03
.04
.03
.03
-.06
-.10
-.10
.02
.04
.04
.05
-.05
-.05
Response surface parameters
a
1 slope LOC
-.49***
-.43***
-.43***
-.44***
-.45***
-.45***
-.12
-.10
-.10
.29***
.32***
.32***
.29***
.28***
.28***
a
2 curve LOC
.15
.24***
.24***
.17**
.21***
.21***
.03
-.03
-.03
-.02
-.10**
-.10**
-.04
-.09*
-.09*
a
3 slope LOIC
-.19
-.28
-.28
.03
-.10
-.10
.07
-.10
-.10
.00
.06
.06
.07
.03
.03
a
4 curve LOIC
-.16
-.03
-.03
-.13
-.01
-.01
-.25**
-.14
-.14
.12
.19*
.19*
.16*
.06
.06
R
2
.16***
.10***
.11***
.14***
.12***
.12***
.06***
.03
.03
.17***
.20***
.20***
.16***
.08
.13***
Note. * p<.05, ** p<.01, ***p<.001
23
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Table S13.
Sample 2: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need satisfaction.
Vitality
Life Satisfaction
Sleep Quality
Depression
Anxiety
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
.25**
.21**
.25***
.24***
.16*
.19***
.07
.03
.00
-.08
-.03
-.13**
-.04
-.04
-.15***
b
2 SMU
.19**
.10
.04
.10
.03
.07
.09
.09
.10
-.10*
-.03
.00
-.20**
*
-.06
-.01
b
3 offline
2
-.03
-.03
-.04
-.05
-.10*
-.05
-.05
-.01
-.04
.04
.06
.10***
.08**
.06
.05
b
4 offline x SMU
.04
.06
-.03
.05
.11
.04
.02
-.05
.06
-.09*
-.06
-.08
-.06
-.06
-.05
b
5 SMU
2
.00
-.08*
-.01
-.04
-.09
.00
-.02
.00
-.02
.04
.08*
.01
.01
.07
.02
Response surface parameters
a
1 slope LOC
.44**
*
.30***
.29***
.34***
.19*
.27***
.16**
.12
.10
-.17**
*
-.07
-.13**
-.24**
*
-.10
-.16***
a
2 curve LOC
.02
-.05
-.08
-.03
-.08
-.10
-.05
-.06
-.00
-.01
.08
.03
.04
.07
.03
a
3 slope LOIC
.06
.11
.22
.14
.14
.12
-.02
-.06
-.10
.02
.00
-.13
.16*
.03
-.14
a
4 curve LOIC
-.06
-.16
-.02
-.13
-.30*
-.08
-.10
.03
-.12
.16*
.19
.19*
.15*
.18*
.12
R
2
.24**
*
.19***
.16***
.22***
.16**
*
.12***
.10**
.05
.05
.14***
.12***
.14***
.24***
.12***
.11***
24
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Note. * p<.05, ** p<.01, ***p<.001
Table S14.
Sample 2: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need frustration.
Vitality
Life Satisfaction
Sleep Quality
Depression
Anxiety
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
-.09
-.04
-.28***
-.15
-.19**
-.36***
-.08
-.20**
-.03
.04
.08
.24***
.03
.07
.19***
b
2 SMU
-.11
-.24***
-.07
-.06
-.20**
.03
-.06
.02
-.09
.12
.16***
.01
.15**
.22***
.12**
b
3 offline
2
-.07
-.04
.02
.02
.02
.03
-.09
-.01
-.04
.11*
.07**
.06*
.06
.03
-.01
b
4 offline x SMU
.23**
.09
-.01
.18**
-.01
-.09
.05
-.02
.12*
.11**
.04
.03
-.17**
-.02
.03
b
5 SMU
2
-.11*
.04
-.01
-.06
.10***
.06
.01
.03
-.05
-.20**
-.07***
.02
.02
-.09
-.02
Response surface parameters
a
1 slope LOC
-.20*
-.28***
-.35***
-.21**
-.40***
-.33***
-.15*
-.18**
-.12
.16***
.24***
.25***
.18***
.29***
.30***
a
2 curve LOC
.05
.09
.00
.14**
.10*
.01
-.03
.00
.04
-.05
.04
.11***
-.08
-.08
-.00
a
3 slope LOIC
.02
.20
-.22
-.09
.01
-.40***
-.02
-.22
.06
-.07
-.08
.23**
-.12
-.14
.07
a
4 curve LOIC
-.41**
-.09
.02
-.22
.13*
.18
-.14
.03
-.21
.36***
-.04
.04
.26**
-.03
-.06
R
2
.14***
.11***
.16***
.13***
.16***
.18***
.11***
.10**
.06
.24***
.23***
.36***
.17***
.18***
.23***
Note. * p<.05, ** p<.01, ***p<.001
25
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Table S15.
Sample 3: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need satisfaction.
Vitality
Life Satisfaction
Sleep Quality
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
.41***
.36***
.40***
-.44***
.41***
.44***
.14***
.11***
.14***
b
2 SMU
.06***
.08***
.08***
.07***
.10***
.04*
.02
.01
.01
b
3 offline
2
.03*
.07***
.06***
.02
.05***
.03*
-.01
-.01
.02
b
4 offline x SMU
.05***
.03
.03***
.03
.04*
.04*
.03*
.03
.03**
b
5 SMU
2
-.01
-.01
.01
-.01
.01
-.01
-.01
-.01
-.01
Response surface parameters
a
1 slope LOC
.47***
.44***
.47***
.52***
.51***
.48***
.17***
.12***
.15***
a
2 curve LOC
.07***
.09***
.08***
.04
.10***
.07***
.01
.01
.03**
a
3 slope LOIC
.34***
.28***
.32***
.37***
.30***
.39***
.12***
.11***
.13***
a
4 curve LOIC
-.03
.03
.03
-.02
.02
-.01
-.04
-.05
-.03
R
2
.16***
.12***
.17***
.17***
.13***
.16***
.04***
.02***
.04***
26
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Note. * p<.05, ** p<.01, ***p<.001
Table S16.
Sample 3: Results of Polynomial Regression Analysis with Response Surface Analyses Predicting Mental Health Outcomes based on autonomy-, relatedness-, and competence need frustration.
Vitality
Life Satisfaction
Sleep Quality
Sample
Aut
Rel
Com
Aut
Rel
Com
Aut
Rel
Com
Polynomial regression coefficients
b
1 offline
.23***
-.20**
*
-.34***
-.25***
-.27**
*
-.36***
-.09***
-.09**
*
-.13***
b
2 SMU
-.05*
-.03
-.08***
-.07**
-.03
.12***
-.04*
.01
-.05***
b
3 offline
2
-.05***
-.01
-.05**
-.04**
.00
-.07***
-.02
-.00
-.03**
b
4 offline x SMU
.04*
.06**
.04*
.04*
.04
.06**
.01
.01
.03*
b
5 SMU
2
-.01
-.07**
*
-.03*
-.03
-.05**
-.04*
-.01
-.02
.02
Response surface parameters
a
1 slope LOC
-.28***
-.22**
*
-.43***
-.32***
-.30**
*
-.48***
-.13***
-.08**
*
-.18***
a
2 curve LOC
-.02
-.02
-.05**
-.04
-.02
-.07***
-.02
-.01
-.02
a
3 slope LOIC
-.18***
-.17**
*
-.26***
-.17***
-.23**
*
-.24***
-.06
-.09**
-.08***
a
4 curve LOIC
-.09**
-.14**
-.12***
-.11***
-.08*
-.17***
-.04
-.03
-.09**
27
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
*
R
2
.10***
.06***
.16***
.10***
.08***
.18***
.04***
.02***
.06***
Note. * p<.05, ** p<.01, ***p<.001
28
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
6.
Figures response surface analyses
6.1. Need satisfaction Figure S1.
Response surface for the polynomial regression of need satisfaction predicting vitality in Sample 1.
Figure S2
. Response surface for the polynomial regression of need satisfaction predicting life satisfaction in Sample 1.
29
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S3
. Response surface for the polynomial regression of need satisfaction predicting sleep quality in Sample 1.
Figure S4.
Response surface for the polynomial regression of need satisfaction predicting depression in Sample 1.
30
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S5
. Response surface for the polynomial regression of need satisfaction predicting anxiety in Sample 1.
Figure S6.
Response surface for the polynomial regression of need satisfaction predicting vitality in Sample 2.
31
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S7
. Response surface for the polynomial regression of need satisfaction predicting life satisfaction in Sample 2.
Figure S8
. Response surface for the polynomial regression of need satisfaction predicting sleep quality in Sample 2.
32
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S9.
Response surface for the polynomial regression of need satisfaction predicting depression in Sample 2.
Figure S10
. Response surface for the polynomial regression of need satisfaction predicting anxiety in Sample 2.
33
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S11.
Response surface for the polynomial regression of need satisfaction predicting vitality in Sample 3.
34
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S12
. Response surface for the polynomial regression of need satisfaction predicting life satisfaction in Sample 3.
Figure S13
. Response surface for the polynomial regression of need satisfaction predicting sleep quality in Sample 3.
35
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
6.2. Need frustration Figure S14
*
.
Response surface for the polynomial regression of need frustration predicting vitality in Sample 1
*
Figure S15
. Response surface for the polynomial regression of need frustration predicting life satisfaction in Sample 1.
36
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S16*
. Response surface for the polynomial regression of need frustration predicting sleep quality in Sample 1.
Figure S17.
Response surface for the polynomial regression of need frustration predicting depression in Sample 1.
37
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S18
. Response surface for the polynomial regression of need frustration predicting anxiety in Sample 1.
Figure S19*.
Response surface for the polynomial regression of need frustration predicting vitality in Sample 2.
Figure S20
. Response surface for the polynomial regression of need frustration predicting life satisfaction in Sample 2.
38
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S21
. Response surface for the polynomial regression of need frustration predicting sleep quality in Sample 2.
Figure S22.
Response surface for the polynomial regression of need frustration predicting depression in Sample 2.
39
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S23
. Response surface for the polynomial regression of need frustration predicting anxiety in Sample 2.
40
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
Figure S24.
Response surface for the polynomial regression of need frustration predicting vitality in Sample 3.
Figure S25
. Response surface for the polynomial regression of need frustration predicting life satisfaction in Sample 3.
Figure S26
. Response surface for the polynomial regression of need frustration predicting sleep quality in Sample 3
41
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
*Note that in Figure S14, S16 and S19 an additional curvilinear effect (a2) was significant on
the LOC. Here, response surface figures suggested that when offline and SMU frustration had
similar values either at the low-end (i.e., front corner) or at the high-end (i.e., upper corner)
this yielded somewhat higher scores on well-being. A finding that would suggest that need
frustration positively relates to well-being would be unexpected and opposed to SDT’s main
claims (Ryan & Deci, 2023). However, these effects should be interpreted very cautiously
given that no significance can be derived from the response surface figures and because
situation on the LOC with high values for need frustration in both domains falls outside of the
bagplot, a multivariate boxplot which depicts the position of the inner 50% of the
42
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
observations (Rousseeuw & Turkey, 1999). Thus, the values presented in the upper corner are
most likely extrapolations with no actual observation (Tufte, 2001).
43
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
44
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
SMU and offline Need-based Experiences
Supplementary Material
45
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Related Documents
Related Questions
what is nominal (categorial) data?
arrow_forward
Define qualitative data?
arrow_forward
Are there a difference in the amount of discipline referrals between girls and boys with autism spectrum disorders?
outcome variable
Predictor( grouping) variable
arrow_forward
Pose a problem or question of interest that requires the organization and analysis of a suitable set of qualitative data (at least two variables).
arrow_forward
Why Mode value is one of the given set of data values?
arrow_forward
What is the difference between qualitative (categorical) data and quantitative data? Provide examples of each.
arrow_forward
What is determining the worth of data?
Evaluation
Validity
Results
arrow_forward
How can surveys be used to address descriptive and/or causal research questions? What are some of the advantages of using surveys to collect data? What about the disadvantages?
arrow_forward
SEE MORE QUESTIONS
Recommended textbooks for you
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Holt Mcdougal Larson Pre-algebra: Student Edition...
Algebra
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Related Questions
- Pose a problem or question of interest that requires the organization and analysis of a suitable set of qualitative data (at least two variables).arrow_forwardWhy Mode value is one of the given set of data values?arrow_forwardWhat is the difference between qualitative (categorical) data and quantitative data? Provide examples of each.arrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillBig Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin HarcourtHolt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGAL
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Holt Mcdougal Larson Pre-algebra: Student Edition...
Algebra
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL