For most, Overall Mood is generally highest after a total of 34 minutes of Time Spent On Social Networking over the previous 7 days.
Trait Correlation Between Time Spent On Social Networking and Overall Mood
Time Spent On Social Networking Distribution
Average Time Spent On Social Networking by Day of Week
Average Time Spent On Social Networking by Month
Overall Mood Distribution
Average Overall Mood by Day of Week
Average Overall Mood by Month
Aggregated data from 22 study participants suggests with a medium degree of confidence (p=0.20141350374427, 95% CI -3.003 to 2.817) that Time Spent On Social Networking has a very weakly negative predictive relationship (R=-0.0929) with Overall Mood. The highest quartile of Overall Mood measurements were observed following an average 34 minutes Time Spent On Social Networking per day. The lowest quartile of Overall Mood measurements were observed following an average 0.9030622251818 h Time Spent On Social Networking per day.
The objective of this study is to determine the nature of the relationship (if any) between Time Spent On Social Networking and Overall Mood. Additionally, we attempt to determine the Time Spent On Social Networking values most likely to produce optimal Overall Mood values.
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This study is based on data donated by 22 participants. Thus, the study design is equivalent to the aggregation of 22 separate n=1 observational natural experiments.
It was assumed that 0 hours would pass before a change in Time Spent On Social Networking would produce an observable change in Overall Mood. It was assumed that Time Spent On Social Networking could produce an observable change in Overall Mood for as much as 7 days after the stimulus event.
As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply correlation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence. The list of the criteria is as follows:
1. Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal.
2. Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.
3. Specificity: Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.
4. Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).
5. Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.
6. Plausibility: A plausible mechanism between cause and effect is helpful.
7. Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect.
8. Experiment: Occasionally it is possible to appeal to experimental evidence.
9. Analogy: The effect of similar factors may be considered.
The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 70 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Time Spent On Social Networking values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate. Furthermore, it will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.
|Cause Variable Name||Time Spent On Social Networking|
|Effect Variable Name||Overall Mood|
|Sinn Predictive Coefficient||0.041585269238615|
|Forward Pearson Correlation Coefficient||-0.0929|
|Critical T Value||1.6838344792136|
|Total Time Spent On Social Networking Over Previous 7 days Before ABOVE Average Overall Mood||34 minutes|
|Total Time Spent On Social Networking Over Previous 7 days Before BELOW Average Overall Mood||54 minutes|
|Duration of Action||7 days|
|Effect Size||very weakly negative|
|Number of Paired Measurements||70|
|Optimal Pearson Product||0.068805645178049|
|Strength of Relationship||2.910127563647|
|Analysis Performed At||2017-12-12|
|Number of Participants||22|
Time Spent On Social Networking Statistics
|Variable Name||Time Spent On Social Networking|
|Analysis Performed At||2018-11-16|
|Duration of Action||7 days|
|Maximum Allowed Value||7 days|
|Minimum Allowed Value||0 seconds|
|Number of Correlations||509|
|Number of Measurements||20512|
|Onset Delay||0 seconds|
Overall Mood Statistics
|Variable Name||Overall Mood|
|Analysis Performed At||2018-11-17|
|Duration of Action||24 hours|
|Maximum Allowed Value||5 out of 5|
|Mean||3.1155337108594 out of 5|
|Median||3.1365425423606 out of 5|
|Minimum Allowed Value||1 out of 5|
|Number of Correlations||1151|
|Number of Measurements||606419|
|Onset Delay||0 seconds|
|Unit||1 to 5 Rating|