Making a Grouped-Data Frequency Table
Development of the Iteration Algorithm
Versandkostenfrei!
Versandfertig in 6-10 Tagen
51,99 €
inkl. MwSt.
PAYBACK Punkte
26 °P sammeln!
This study focuses on the development and examination of a new method to construct frequency tables for grouped data. This method is called the iteration algorithm in that it proceeds by successive iterations to determine the four key elements that are essential in building a grouped-data frequency distribution. The algorithm also uses five formulas and stops running as soon as the first solution is attained (for teaching purposes only). Two major interests emerged. The first interest was to evaluate how accurate the iteration algorithm is as a process. The second and main focus of this study ...
This study focuses on the development and
examination of a new method to construct frequency
tables for grouped data. This method is called the
iteration algorithm in that it proceeds by
successive iterations to determine the four key
elements that are essential in building a grouped-
data frequency distribution. The algorithm also uses
five formulas and stops running as soon as the first
solution is attained (for teaching purposes only).
Two major interests emerged. The first interest was
to evaluate how accurate the iteration algorithm is
as a process. The second and main focus of this
study was to assess the effectiveness of the
iteration algorithm as an instructional method. The
findings of the Monte Carlo simulations to address
the first main interest showed that the results
yielded by the iteration algorithm are comparable to
those produced by a well-known statistical package.
To tackle the second aspect of this study, the
the multivariate analysis of covariance results
indicated that the students expressed, on
average, more positive attitudes towards the
iteration algorithm than towards a traditional
method.
examination of a new method to construct frequency
tables for grouped data. This method is called the
iteration algorithm in that it proceeds by
successive iterations to determine the four key
elements that are essential in building a grouped-
data frequency distribution. The algorithm also uses
five formulas and stops running as soon as the first
solution is attained (for teaching purposes only).
Two major interests emerged. The first interest was
to evaluate how accurate the iteration algorithm is
as a process. The second and main focus of this
study was to assess the effectiveness of the
iteration algorithm as an instructional method. The
findings of the Monte Carlo simulations to address
the first main interest showed that the results
yielded by the iteration algorithm are comparable to
those produced by a well-known statistical package.
To tackle the second aspect of this study, the
the multivariate analysis of covariance results
indicated that the students expressed, on
average, more positive attitudes towards the
iteration algorithm than towards a traditional
method.
Andere Kunden interessierten sich für
