Higher Overall Mood Predicts Very Slightly Higher Intelligence Activities for Population
Contents
Mike Sinn
PRINCIPAL INVESTIGATOR
Mike Sinn

Variables

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Overall Mood 7137
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Intelligence Activities 173

Categories

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Emotions 2028
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Activities 1637

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Tags

High Confidence
Very Weak Effect Size
Positive Relationship
Population Study
cause image gauge image effect image
Participants reported a 110.5% average increase in Intelligence Activities following above average Overall Mood.
Abstract

Abstract

Intelligence Activities was generally 82% higher than average after an average of 3.47 out of 5 of Overall Mood over the previous 24 hours.

Aggregated data from 10 study participants suggests with a HIGH degree of confidence (p=0.264, 95% CI -0.049 to 0.167) that Overall Mood has a very weakly positive predictive relationship (R=0.0592) with Intelligence Activities.

The highest quartile of Intelligence Activities measurements were observed following an average 3.32 out of 5 Overall Mood.

The lowest quartile of Intelligence Activities measurements were observed following an average 3.16 out of 5 of Overall Mood.

After an onset delay of 0 seconds, Intelligence Activities is typically 46% lower than average over the 24 hours following around 3.16 out of 5 Overall Mood.

Objective

Objective

The objective of this study is to determine the nature of the relationship (if any) between Overall Mood and Intelligence Activities. Additionally, we attempt to determine the Overall Mood values most likely to produce optimal Intelligence Activities values.
Participant Instructions

Participant Instructions

Manual Recording Option

A Create a reminder for Overall Mood here and record it daily by enabling notifications or using A the reminder inbox here .


Intelligence Activities Automatic Import of Intelligence Activities via RescueTime

A Get RescueTime here and use it to record your Intelligence Activities. Then, A import your data here .

Manual Recording Option

A Create a reminder for Intelligence Activities here and record it daily by enabling notifications or using A the reminder inbox here .

Design

Design

This study is based on data donated by 10 participants. Thus, the study design is equivalent to the aggregation of 10 separate n=1 observational natural experiments.

Data Analysis

Data Analysis

Overall Mood Pre-Processing

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.

Intelligence Activities Pre-Processing

Intelligence Activities measurement values below 0 seconds were assumed erroneous and removed. Intelligence Activities measurement values above 7 days were assumed erroneous and removed. It was assumed that any gaps in Intelligence Activities data were unrecorded 0 seconds measurement values.

Predictive Analytics

It was assumed that 0 seconds would pass before a change in Overall Mood would produce an observable change in Intelligence Activities.

It was assumed that Overall Mood could produce an observable change in Intelligence Activities for as much as 24 hours after the stimulus event.

Statistical Significance

Statistical Significance

Using a two-tailed t-test with alpha = 0.05, it was determined that the change in Intelligence Activities is not statistically significant at a 95% confidence interval. This suggests that the Overall Mood value does not have a significant influence on the Intelligence Activities value.

After treatment, a 111% increase (2 minutes) from the mean baseline 3 minutes was observed. The relative standard deviation at baseline was 357.54%. The observed change was 1.35495 times the standard deviation.

A common rule of thumb considers a change greater than twice the baseline standard deviation on two separate pre-post experiments may be considered significant. This occurrence would have only a 5% likelihood of resulting from random fluctuation (a p-value < 0.05).

Data Sources

Data Sources

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.

Intelligence Activities data was primarily collected using RescueTime. Detailed reports show which applications and websites you spent time on. Activities are automatically grouped into pre-defined categories with built-in productivity scores covering thousands of websites and applications. You can customize categories and productivity scores to meet your needs.

Limitations

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 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.

Criteria For Causal Inference

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 very weakly positive (R = 0.0592) relationship between Overall Mood and Intelligence Activities.

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. 1522 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Overall Mood 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 time-precedence 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 bio-chemical mechanism between cause and effect is critical. This is where human brains excel.

Based on our responses so far,

0 humans feel that there is a plausible mechanism of action for a relationship between Overall Mood and Intelligence Activities.

0 humans feel that any relationship observed between Overall Mood and Intelligence Activities 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.

Plausibility

Plausibility

A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 0 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Overall Mood and Intelligence Activities is coincidental.

Relationship Statistics

Property Value
Cause Variable Name Overall Mood
Effect Variable Name Intelligence Activities
Sinn Predictive Coefficient 0.0018710768546977
Confidence Level HIGH
Confidence Interval 0.10789868646169
Forward Pearson Predictive Coefficient 0.0592
Critical T Value 1.6751
Average Overall Mood Over Previous 24 hours Before ABOVE Average Intelligence Activities 3.32 out of 5
Average Overall Mood Over Previous 24 hours Before BELOW Average Intelligence Activities 3.16 out of 5
Duration of Action 24 hours
Effect Size very weakly positive
Number of Paired Measurements 1522
Optimal Pearson Product 0.0443854753293
P Value 0.26429715994507
Statistical Significance 0.3944
Strength of Relationship 0.10789868646169
Study Type population
Analysis Performed At 2021-08-30
Number of Participants 10

Overall Mood Info

Property Value
Variable Name Overall Mood
Aggregation Method MEAN
Analysis Performed At 2020-09-12
Duration of Action 24 hours
Kurtosis 3.3832907631011
Maximum Allowed Value 5 out of 5
Mean 3.1202433341482 out of 5
Median 3.1415600073553 out of 5
Minimum Allowed Value 1 out of 5
Number of Aggregate Predictors 6425
Number of Aggregate Outcomes 712
Number of Measurements 617070
Number of Measurements (including those generated by tagged, joined, or child variables) 561596
Public true
Onset Delay 0 seconds
Standard Deviation 0.38176118810538
Unit 1 to 5 Rating
User Variables 9142
UPC 767674073845
Variable Category Emotions
Variable ID 1398
Variance 0.30220747449488

Intelligence Activities Info

Property Value
Variable Name Intelligence Activities
Aggregation Method SUM
Analysis Performed At 2020-10-11
Duration of Action 7 days
Filling Value 0
Kurtosis 158.94716616671
Maximum Allowed Value 7 days
Mean 15 minutes
Median 2 seconds
Minimum Allowed Value 0 seconds
Number of Aggregate Predictors 16
Number of Aggregate Outcomes 157
Number of Measurements 12360
Number of Measurements (including those generated by tagged, joined, or child variables) 2323
Public true
Onset Delay 0 seconds
Standard Deviation 1.0992603676391
Unit Hours
User Variables 59
Variable Category Activities
Variable ID 5956887
Variance 7.8810676497271