APPLICATION OF STATISTICAL CONCEPTS IN THE DETERMINATION OF WEIGHT VARIATION IN SAMPLES
APPLICATION OF STATISTICAL CONCEPTS IN THE DETERMINATION OF WEIGHT VARIATION IN SAMPLES
D. E. BIACORA
DEPARTMENT OF MINING, METALLURGICAL AND MATERIALS ENGINEERING
COLLEGE OF ENGINEERING, UNIVERSITY OF THE PHILIPPINES, DILIMAN, QUEZON CITY, PHILIPPINES
DATE PERFORMED: 19 November 2013
INTRODUCTION Analytical chemistry involves the separation, identification and determination of amounts of components in a particular sample. Accuracy and precision are important in data acquisition to be able to acquire substantial results in the end of the experiment. To attain such goal, replication of measurements must be performed. The reliability of the measurements may then be evaluated through various statistical parameters [1]. Among the acquired data in the course of the experiment, it is possible that not all data are considered valid. Invalid data are called outliers, values that significantly differ among others in the set of data [2]. Before doing the statistical calculations, suspect values, which are the lowest and highest data obtained are evaluated in terms of its acceptability through the Q-test. It makes use of the tabulated critical values for different confidence levels in which the resultant value for the said test should not exceed, otherwise the datum is considered invalid and cannot be included in the course of the following calculations.
Where Xq is the highest or the lowest datum, Xn is the closest numerical value to the suspect values and R is the range of the data set. The sample mean is considered as the most valid estimate of the true value that is considered in the course of the experiment. It is considered as the norm in finding the probable location of the center of the data set since it is the value in between the extremes of the data. This is acquired by dividing the summation of the data within the set by the number of data added altogether [3].
Where is the mean value and represents the individual datum in the
D. E. BIACORA
DEPARTMENT OF MINING, METALLURGICAL AND MATERIALS ENGINEERING
COLLEGE OF ENGINEERING, UNIVERSITY OF THE PHILIPPINES, DILIMAN, QUEZON CITY, PHILIPPINES
DATE PERFORMED: 19 November 2013
INTRODUCTION Analytical chemistry involves the separation, identification and determination of amounts of components in a particular sample. Accuracy and precision are important in data acquisition to be able to acquire substantial results in the end of the experiment. To attain such goal, replication of measurements must be performed. The reliability of the measurements may then be evaluated through various statistical parameters [1]. Among the acquired data in the course of the experiment, it is possible that not all data are considered valid. Invalid data are called outliers, values that significantly differ among others in the set of data [2]. Before doing the statistical calculations, suspect values, which are the lowest and highest data obtained are evaluated in terms of its acceptability through the Q-test. It makes use of the tabulated critical values for different confidence levels in which the resultant value for the said test should not exceed, otherwise the datum is considered invalid and cannot be included in the course of the following calculations.
Where Xq is the highest or the lowest datum, Xn is the closest numerical value to the suspect values and R is the range of the data set. The sample mean is considered as the most valid estimate of the true value that is considered in the course of the experiment. It is considered as the norm in finding the probable location of the center of the data set since it is the value in between the extremes of the data. This is acquired by dividing the summation of the data within the set by the number of data added altogether [3].
Where is the mean value and represents the individual datum in the
References: of the Philippines Diliman. 2007. pp. 8-12. Brooks/Cole – Thomson Learning. 2004. pp