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The American Association of School Administrators (AASA), founded in 1865, is the professional organization for more than 14,000 educational leaders across the United States. [1] AASA's members are chief executive officers and senior-level administrators from school districts in every region of the country, in rural, urban, and suburban settings.
Additionally, they would have either needed to receive at least a score of 3 on two Advanced Placement tests or at least a score of 4 on two International Baccalaureate exams. Qualified students would receive a full state university tuition waiver valid for one year following graduation from high school.
Illustration of the Kolmogorov–Smirnov statistic. The red line is a model CDF, the blue line is an empirical CDF, and the black arrow is the KS statistic.. In statistics, the Kolmogorov–Smirnov test (also K–S test or KS test) is a nonparametric test of the equality of continuous (or discontinuous, see Section 2.2), one-dimensional probability distributions.
In statistical hypothesis testing, a two-sample test is a test performed on the data of two random samples, each independently obtained from a different given population. The purpose of the test is to determine whether the difference between these two populations is statistically significant .
The SAT, Graduate Record Examination (GRE), and Wechsler Intelligence Scale for Children (WISC) compare individual student performance to the performance of a normative sample. Test takers cannot "fail" a norm-referenced test, as each test taker receives a score that compares the individual to others that have taken the test, usually given by a ...
Denny Hamlin led a trio of Toyota drivers — the manufacturer claimed five of the top six spots — in Wednesday's opening practice for the Daytona 500. Hamlin, a three-time Daytona 500 winner ...
The Anderson–Darling test assesses whether a sample comes from a specified distribution. It makes use of the fact that, when given a hypothesized underlying distribution and assuming the data does arise from this distribution, the cumulative distribution function (CDF) of the data can be transformed to what should follow a uniform distribution.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
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