This means that the average Criterion® score at Time 1 was 3.75, and this was significantly different from zero.
The intercept (γ00) was 3.82 and statistically significant, meaning that the average Criterion® score at Time 1 was 3.82, and this was significantly different from zero.
The intercept (γ00) was 3.46 and statistically significant, meaning that the average Criterion® score at Time 1 was adjusted to 3.46 when time was included, and this was significantly different from zero.
This indicates that the average Criterion® score for each class at Time 1 differed by 0.18 points (e.g., if the mean of Class A the best class was 3.76 [see Table 7], the mean of Class B was 3.58 [3.76 − 0.18]).
There is also a positive correlation with the so-called investors' average Design Quality Criteria score (the Investor Design Index).
The overall impact score did not need to be an average of the individual criterion scores; instead, the weight of an individual component, such as high significance or great training potential, could outweigh concerns about other factors, such as innovation.
Their position was also in the startup sweet spot and although noteworthy for being less overconfident, they performed average on most Design Quality Criteria, scoring below average on environmental concerns.
To describe the significance of the criteria, the average significance score (AvSS) of each individual criterion was calculated considering the average of the significance scores from the entire sample.
The criteria were: average reference quality score (based on average BES quality score), reference SNP base quality score, SNP mapping quality score (MQS) (from the BWA mapping software [ 20]), RMD, and FVF (Table 4).
Accordingly, the data were filtered using the following criteria: minimum average quality score: 35 for a windows of 50, number of differences to the primer sequence = 0, maximum number of differences to the barcode sequence = 0, number of ambiguous base calls = 0, maximium homopolymer length = 8.
In the "complex problem" treatment, four more criteria were added: Average evaluation score of lecturers by students in previous semesters (maximize), percentage of students who passed the course having the lowest pass rate in the selected course schedule (maximize), prospective average number of students in class (minimize), and average grade obtained by students in past courses.
