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A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how to conduct the statistical aspects of an experiment and which action to take for each possible outcome. Choosing the decision function needs a loss function to be defined which assigns numerical values to making bad or good decisions. Explicitly a general loss function is denoted by L d; expressing how bad it would be to make decision d if the parameter value were. A quadratic loss function, it could be defined as and a bilinear loss function as
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Lie factor : A measure suggested by Tufte for judging the honesty of the graphical presentation of data. Which can be calculated as follows The values close to one are desir
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Non-randomized clinical trial is the clinical trial in which the series of consecutive patients receive a new treatment and those which respond (according to some of the pre-defin
Prognostic scoring system is a technique of combining the prognostic information contained in the number of threat factors, in a manner which best predicts each patient's risk of
Graduation is the term is employed most often in the application of the actuarial statistics to denote procedures by which the set or group of observed probabilities is adjusted t
Incubation period is the time elapsing amongs the receipt of infection and the appearance of the symptoms. The length of the incubation time period depends on the disease, ranging
Random allocation is a technique for creating the treatment and control groups particularly in accordance of the clinical trial. Subjects receive the active treatment or the place
Median is the value in a set of the ranked observations which divides the data into two parts of equal size. When there are an odd number of observations the median is middle v
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
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