This individual's Overall Mood is generally 6.8% higher after 6 tablets Creatine Fuel Stack over the previous 7 days.


Abstract
This individual's Overall Mood is generally 5% higher than normal after a total of 6 tablets Creatine Fuel Stack over the previous 7 days. This individual's data suggests with a low degree of confidence (p=0.24509384684212, 95% CI 0.209 to 0.477) that Creatine Fuel Stack has a weakly positive predictive relationship (R=0.13) with Overall Mood. The highest quartile of Overall Mood measurements were observed following an average 2 tablets Creatine Fuel Stack per day. The lowest quartile of Overall Mood measurements were observed following an average 1.3846153846154 tablets Creatine Fuel Stack per day. Overall Mood is generally 2% lower than normal after a total of 1.3846153846154 tablets of Creatine Fuel Stack over the previous 7 days. Overall Mood is generally 5% higher after a total of 2 tablets of Creatine Fuel Stack over the previous 7 days.
Objective
The objective of this study is to determine the nature of the relationship (if any) between Creatine Fuel Stack and Overall Mood. Additionally, we attempt to determine the Creatine Fuel Stack values most likely to produce optimal Overall Mood values.
Participant Instructions
Record your Creatine Fuel Stack daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Overall Mood daily in the reminder inbox or using the interactive web or mobile notifications.
Record your Overall Mood daily in the reminder inbox or using the interactive web or mobile notifications.
Design
This study is based on data donated by one participant. Thus, the study design is consistent with an n=1 observational natural experiment.
Data Analysis
Creatine Fuel Stack PreProcessing
Creatine Fuel Stack measurement values below 0 tablets were assumed erroneous and removed. Creatine Fuel Stack measurement values above 20 tablets were assumed erroneous and removed. It was assumed that any gaps in Creatine Fuel Stack data were unrecorded 0 tablets measurement values.
Overall Mood PreProcessing
Overall Mood measurement values below 1 out of 5 were assumed erroneous and removed. Overall Mood measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Overall Mood so any gaps in data were just not analyzed instead of assuming zero values for those times.
Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Creatine Fuel Stack would produce an observable change in Overall Mood. It was assumed that Creatine Fuel Stack could produce an observable change in Overall Mood for as much as 7 days after the stimulus event.
Data Quantity
3 raw Creatine Fuel Stack measurements with 4 changes spanning 17 days from 20130722 to 20130808 were used in this analysis. 14146 raw Overall Mood measurements with 1268 changes spanning 2656 days from 20120506 to 20190813 were used in this analysis.
Creatine Fuel Stack measurement values below 0 tablets were assumed erroneous and removed. Creatine Fuel Stack measurement values above 20 tablets were assumed erroneous and removed. It was assumed that any gaps in Creatine Fuel Stack data were unrecorded 0 tablets measurement values.

Overall Mood PreProcessing
Overall Mood measurement values below 1 out of 5 were assumed erroneous and removed. Overall Mood measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Overall Mood so any gaps in data were just not analyzed instead of assuming zero values for those times.

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Creatine Fuel Stack would produce an observable change in Overall Mood. It was assumed that Creatine Fuel Stack could produce an observable change in Overall Mood for as much as 7 days after the stimulus event.

Data Quantity
3 raw Creatine Fuel Stack measurements with 4 changes spanning 17 days from 20130722 to 20130808 were used in this analysis. 14146 raw Overall Mood measurements with 1268 changes spanning 2656 days from 20120506 to 20190813 were used in this analysis.
Statistical Significance
Using a twotailed ttest with alpha = 0.05, it was determined that the change in Overall Mood is not statistically significant at a 95% confidence interval. This suggests that the Creatine Fuel Stack value does not have a significant influence on the Overall Mood value.After treatment, a 6.8% increase (0.20235468896183 out of 5) from the mean baseline 2.9674865808794 out of 5 was observed. The relative standard deviation at baseline was 22.5%. The observed change was 0.30368208468614 times the standard deviation. A common rule of thumb considers a change greater than twice the baseline standard deviation on two separate prepost experiments may be considered significant. This occurrence would may have only a 5% likelihood of resulting from random fluctuation (a pvalue
Data Sources
Creatine Fuel Stack data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.
Overall Mood data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.
Overall Mood data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.
Limitations
As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply causation. 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 nonexistent 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:
Strength (A.K.A. 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. There is a weakly positive relationship between Creatine Fuel Stack and Overall Mood
Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 57 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Creatine Fuel Stack 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.
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.
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). The confidence in a causal relationship is bolstered by the fact that timeprecedence was taken into account in all calculations.
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.
Plausibility
A plausible biochemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Creatine Fuel Stack and Overall Mood is coincidental.
Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.
Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.
Analogy
The effect of similar factors may be considered.
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:
Strength (A.K.A. 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. There is a weakly positive relationship between Creatine Fuel Stack and Overall Mood
Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 57 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Creatine Fuel Stack 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.
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.
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). The confidence in a causal relationship is bolstered by the fact that timeprecedence was taken into account in all calculations.
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.
Plausibility
A plausible biochemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Creatine Fuel Stack and Overall Mood is coincidental.
Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.
Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.
Analogy
The effect of similar factors may be considered.
Relationship Statistics
Property  Value 

Cause Variable Name  Creatine Fuel Stack 
Effect Variable Name  Overall Mood 
Sinn Predictive Coefficient  0.0077 
Confidence Level  low 
Confidence Interval  0.34255631470905 
Forward Pearson Predictive Coefficient  0.134 
Critical T Value  1.671 
Total Creatine Fuel Stack Over Previous 7 days Before ABOVE Average Overall Mood  2 tablets 
Total Creatine Fuel Stack Over Previous 7 days Before BELOW Average Overall Mood  1.385 tablets 
Duration of Action  7 days 
Effect Size  weakly positive 
Number of Paired Measurements  57 
Optimal Pearson Product  0.030935799851788 
P Value  0.24509384684212 
Statistical Significance  0.0136 
Strength of Relationship  0.34255631470905 
Study Type  individual 
Analysis Performed At  20190813 
Number of Pairs  57 
Number of Raw Predictor Measurements ( Including Tags, Joins, and Children)  3 
Baseline Relative Standard Deviation of Outcome Measurements  22.5 
Experiment Duration (days)  83 
Number of Raw Outcome Measurements  14145 
Z Score  0.30368208468614 
Last Analysis  20190813 
Experiment Began  20130622 21:41:00 
Experiment Ended  20130914 18:30:00 
P Value  0.24509384684212 
Predictor Category  Treatments 
Duration of Action (h)  168 
Onset Delay (h)  0.5 
Significance  0.0136 
Outcome Relative Standard Deviation at Baseline  22.5 
Outcome Standard Deviation at Baseline  0.66633726243999/5 
Outcome Mean at Baseline  2.9674865808794/5 
Average Followup Change From Baseline  6.8& 
Average Absolute Followup Change From Baseline  3.1698412698413/5 
Z Score  0.30368208468614 
Average Predictor Treatment Value  6tablets over 7 days 
Creatine Fuel Stack Statistics
Property  Value 

Variable Name  Creatine Fuel Stack 
Aggregation Method  SUM 
Analysis Performed At  20190813 
Duration of Action  7 days 
Kurtosis  3.6526610644258 
Maximum Allowed Value  20 tablets 
Mean  1.0588 tablets 
Median  0 tablets 
Minimum Allowed Value  0 tablets 
Number of Changes  4 
Number of Correlations  4 
Number of Measurements  3 
Onset Delay  30 minutes 
Standard Deviation  2.3577157439801 
Unit  Tablets 
UPC  885151365402 
Variable ID  1295 
Variance  5.5588235294118 
Overall Mood Statistics
Property  Value 

Variable Name  Overall Mood 
Aggregation Method  MEAN 
Analysis Performed At  20190813 
Duration of Action  24 hours 
Kurtosis  6.8518821840864 
Maximum Allowed Value  5 out of 5 
Mean  2.9074 out of 5 
Median  3 out of 5 
Minimum Allowed Value  1 out of 5 
Number of Changes  1268 
Number of Correlations  4553 
Number of Measurements  14146 
Onset Delay  0 seconds 
Standard Deviation  0.52138376175167 
Unit  1 to 5 Rating 
UPC  767674073845 
Variable ID  1398 
Variance  0.27184102701832 
Tracking Creatine Fuel Stack
Record your Creatine Fuel Stack daily in the reminder inbox or using the interactive web or mobile notifications.Tracking Overall Mood
Record your Overall Mood daily in the reminder inbox or using the interactive web or mobile notifications.

Principal Investigator  Mike Sinn