This individual's Time Spent On Reference And Learning is generally highest after a daily total of 20 minutes of Meditation over the previous 7 days.


Abstract
This individual's Time Spent On Reference And Learning is generally 27% higher than normal after a total of 20 minutes Meditation over the previous 7 days. This individual's data suggests with a high degree of confidence (p=2.8794346366344E6, 95% CI 0.055 to 0.341) that Meditation has a weakly positive predictive relationship (R=0.14) with Time Spent On Reference And Learning. The highest quartile of Time Spent On Reference And Learning measurements were observed following an average 18 minutes Meditation per day. The lowest quartile of Time Spent On Reference And Learning measurements were observed following an average 11.374179431072 min Meditation per day.Time Spent On Reference And Learning is generally 14% lower than normal after a total of 11 minutes of Meditation over the previous 7 days. Time Spent On Reference And Learning is generally 27% higher after a total of 18 minutes of Meditation over the previous 7 days.
Objective
The objective of this study is to determine the nature of the relationship (if any) between Meditation and Time Spent On Reference And Learning. Additionally, we attempt to determine the Meditation values most likely to produce optimal Time Spent On Reference And Learning values.
Participant Instructions
Record your Meditation daily in the reminder inbox or using the interactive web or mobile notifications.
Get RescueTime here and use it to record your Time Spent On Reference And Learning. Once you have a RescueTime account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Get RescueTime here and use it to record your Time Spent On Reference And Learning. Once you have a RescueTime account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
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
Meditation PreProcessing
Meditation measurement values below 0 microseconds were assumed erroneous and removed. Meditation measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Meditation data were unrecorded 0 microseconds measurement values.
Time Spent On Reference And Learning PreProcessing
Time Spent On Reference And Learning measurement values below 0 seconds were assumed erroneous and removed. Time Spent On Reference And Learning measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Time Spent On Reference And Learning data were unrecorded 0 seconds measurement values.
Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Meditation would produce an observable change in Time Spent On Reference And Learning. It was assumed that Meditation could produce an observable change in Time Spent On Reference And Learning for as much as 7 days after the stimulus event.
Data Quantity
916 raw Meditation measurements with 263 changes spanning 1889 days from 20140429 to 20190630 were used in this analysis. 560 raw Time Spent On Reference And Learning measurements with 557 changes spanning 682 days from 20160603 to 20180416 were used in this analysis.
Meditation measurement values below 0 microseconds were assumed erroneous and removed. Meditation measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Meditation data were unrecorded 0 microseconds measurement values.

Time Spent On Reference And Learning PreProcessing
Time Spent On Reference And Learning measurement values below 0 seconds were assumed erroneous and removed. Time Spent On Reference And Learning measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Time Spent On Reference And Learning data were unrecorded 0 seconds measurement values.

Predictive Analytics
It was assumed that 0.5 hours would pass before a change in Meditation would produce an observable change in Time Spent On Reference And Learning. It was assumed that Meditation could produce an observable change in Time Spent On Reference And Learning for as much as 7 days after the stimulus event.

Data Quantity
916 raw Meditation measurements with 263 changes spanning 1889 days from 20140429 to 20190630 were used in this analysis. 560 raw Time Spent On Reference And Learning measurements with 557 changes spanning 682 days from 20160603 to 20180416 were used in this analysis.
Data Sources
Meditation 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.
Time Spent On Reference And Learning data was primarily collected using RescueTime. Detailed reports show which applications and websites you spent time on. Activities are automatically grouped into predefined categories with builtin productivity scores covering thousands of websites and applications. You can customize categories and productivity scores to meet your needs.
Time Spent On Reference And Learning data was primarily collected using RescueTime. Detailed reports show which applications and websites you spent time on. Activities are automatically grouped into predefined categories with builtin productivity scores covering thousands of websites and applications. You can customize categories and productivity scores to meet your needs.
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 Meditation and Time Spent On Reference And Learning
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. 713 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Meditation 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 Meditation and Time Spent On Reference And Learning 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 Meditation and Time Spent On Reference And Learning
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. 713 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Meditation 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 Meditation and Time Spent On Reference And Learning 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  Meditation 
Effect Variable Name  Time Spent On Reference And Learning 
Sinn Predictive Coefficient  0.0871 
Confidence Level  high 
Confidence Interval  0.19780025677389 
Forward Pearson Correlation Coefficient  0.143 
Critical T Value  1.646 
Total Meditation Over Previous 7 days Before ABOVE Average Time Spent On Reference And Learning  18 minutes 
Total Meditation Over Previous 7 days Before BELOW Average Time Spent On Reference And Learning  11 minutes 
Duration of Action  7 days 
Effect Size  weakly positive 
Number of Paired Measurements  713 
Optimal Pearson Product  0.054004067488632 
P Value  2.8794346366344E6 
Statistical Significance  0.9937 
Strength of Relationship  0.19780025677389 
Study Type  individual 
Analysis Performed At  20190615 
Meditation Statistics
Property  Value 

Variable Name  Meditation 
Aggregation Method  SUM 
Analysis Performed At  20190701 
Duration of Action  7 days 
Kurtosis  13.850137687697 
Maximum Allowed Value  7 days 
Mean  80 seconds 
Median  0 microseconds 
Minimum Allowed Value  0 microseconds 
Number of Changes  263 
Number of Correlations  278 
Number of Measurements  916 
Onset Delay  30 minutes 
Standard Deviation  3.5609044605963 
Unit  Minutes 
UPC  640791683572 
Variable ID  85055 
Variance  12.680040577494 
Time Spent On Reference And Learning Statistics
Property  Value 

Variable Name  Time Spent On Reference And Learning 
Aggregation Method  SUM 
Analysis Performed At  20190412 
Duration of Action  7 days 
Kurtosis  24.827380230801 
Maximum Allowed Value  7 days 
Mean  86 minutes 
Median  64 minutes 
Minimum Allowed Value  0 seconds 
Number of Changes  557 
Number of Correlations  945 
Number of Measurements  560 
Onset Delay  0 seconds 
Standard Deviation  1.6463173712562 
Unit  Hours 
Variable ID  111642 
Variance  2.7103608868998 
Tracking Meditation
Record your Meditation daily in the reminder inbox or using the interactive web or mobile notifications.Tracking Time Spent On Reference And Learning
Get RescueTime here and use it to record your Time Spent On Reference And Learning. Once you have a RescueTime account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Principal Investigator  Mike Sinn