What Is a SAMPLE History?

Sample data is a method proposed for the problem that the probability distribution characteristics of small sample test data can sometimes not be determined, and traditional probability statistics cannot provide corresponding parameter estimation methods.

The characteristics of the probability distribution for small sample test data can sometimes not be determined. Traditional

The most frequent sample value in the sample data set is called

Example: Calculating Means and Standard Deviations

Solution: Before analysis, it is best to create an external data file. If you do not create an external data file, you can also enter data in the job stream. In general, when the amount of data is relatively large and it is possible to reuse it, it is best to create a data file. Here we create an external data file called 2-1data.dat and store it in the A drive. The most basic procedure for describing data using the MEANS process is as follows ^[2] :

options linesize = 76;

data abc;

infile 'a: \ 2-1data.dat';

input x;

run;

proc means;

run;

After submitting the SAS run, the results are shown in Table 1:

Table 1 Output results

The SAS System
Analysis Variable: XN	250
Mean	63.2760000
Std Dev	3.0139941
Minimum	55.0000000
Maximum	70.0000000

The printed results include: number of data, average, standard deviation, minimum and maximum. This is the basic result of the MEANS statement by default. If a more detailed description of the data is required, the required statistics should be indicated. The statistics calculated using the MEANS process are also listed here. The statistics calculated by the MEANS process are expressed by keywords. These keywords and their meanings are as follows:

N: the number of input observations;

NMISS: the number of missing values contained in each variable;

MEAN: the average number of variables;

STD: standard deviation of the variable;

MIN: the minimum value of the variable;

MAX: the maximum value of the variable;

RANGE: the range of the variable;

SUM: the sum of all values of the variable;

VAR: the variance of the variable;

USS: the sum of squares of the raw data for each variable (uncorrected sum of squares);

CSS: Sum of squared deviations (corrected sum of squares) for each variable;

CV: coefficient of variation STDERR: standard error of each variable (standard deviation of the mean);

T: t value when H0: = 0;

PRT: under the assumption of H0: = 0, the probability that the statistic t is greater than the absolute value of the critical value of t;

SKEWNESS: skewness;

KURTOSIS: kurtosis;

CLM: the upper and lower limits of the confidence interval;

LCLM: lower limit of the confidence interval;

UCLM: the upper bound of the confidence interval;

In addition, there are 12 options in the PROC MEANS statement, of which the main options are as follows:

DATA = (SAS data set): indicates the name of the SAS data set, if omitted, the most recently generated data set will be used;

MAXDEC = (number): indicates the maximum number of digits (0-8) in the decimal part of the output result, which is 8 digits by default;

FW = (field width): indicates the field width of each statistic in the printed result, which is 12 by default;

VARDEF = (DF / N): VARDEF = DF is the default value, which means that n-1 is used as the denominator when calculating variance;

VARDEF = N means to use the number of observations n as the denominator when calculating the variance;

ALPHA = ( value): Indicate the significance level used when calculating the confidence interval.