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Computer-assisted interviews: A method or technique of interviewing subjects in which the interviewer reads the question from the computer screen instead of the printed page, and makes use of the keyboard to enter the answer. Skip patterns (that is 'if so-and-so, go to query such-and-such') are built into program, so that the screen automatically shows the appropriate question. Checks can be built in and the immediate warning given if a reply lies outside the acceptable range or is inconsistent with earlier replies; revision of earlier replies is permitted, with the automatic return to the current question. The responses are entered straightly on to the computer record, avoiding the requirement for subsequent coding and the data entry. The program can make automatic selection of the subjects who need additional procedures, like supplementary questionnaires, special tests, or follow-up visits.
Command-Line options Compression: C++: ./compress -f myfile.txt [-o myfile.hzip -s Java: sh compress.sh -f myfile.txt [-o myfile.hzip -s] Decompression:
The procedure which targets to use the health and health-related data which precede diagnosis and/or confirmation to identify possible outbreaks of the disease, mobilize a rapid re
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
A standard IQ test has a mean of 98 and a standard deviation of 16. We want to be 99% certain that we are within 8 IQ points of the true mean. Determine the sample size
This is the branch of mathematics which deals with the theory of contests between two or more players under the specified sets of rules. The subject supposes a statistical aspect w
Suppose the graph G is n-connected, regular of degree n, and has an even number of vertices. Prove that G has a one-factor. Petersen's 2-factor theorem (Theorem 5.40 in the note
Auto correlation : The correlation of the internal observations in the time series, generally expressed as a function of the time lag between the observations. It is also used for
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
Mean squarederror is the expected value of square of the difference between an estimator and the true value of the parameter. If the estimator is unbiased then the mean of the squ
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
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