OR = 1.48, 95% CI (1.03-2. 24), Q = 2. 89, V = 8, P> 0.05. Statistics from 7 papers revealed the mean survival rate of TCM group was 335. 4 days, that of chemotherapeutic group 231. 8, test of significance P = 0. 1489. MA results showed that the features of TCM treatment on NSCL were: high stability, low effectiveness, however, with certain dominance.

Results The test of significance between two methods was P>0.05, the coefficient of correlation was r=0.7752, the test of significance was P<0.01, the equation of linear regression between the GB method(X) and the manual method() was =1.1623X+0.0008, the test of significance of coefficient of regression was P<0.01.Conclusion Two kinds of methods had no significant differences.

Using Excel regression analysis system, the method of stepwise analysis and test of significance, this paper has established the regression relation between the collapsible coefficient and some physical properties(w, e_0, γ) for various units in Xi'an region.

The correlation coefficient R and test of significance (F) showed that r was closely related to Sr. The average absolute error of the 102 radii of positive ions was only 0.9 pm with the representative radii of ions, the relative error was 1.1%.

According to statistically analysis of orthogonal experiment results and test of significance level of each factor,optimum conditions for the synthesis of tetrachlorophthalic anhydride by chlorina- ting phthalic anhydride with chlorine gas were obtained,which were as follows:reaction time 12 h,temperature from 80 ℃ to 160 ℃,1∶10∶B 1∶C 2 material molar ratio of phthalic anhydride,industrial solvent,catalyst and chlorine gas.

S-benzyl-L-cysteine can be synthesized by benzyl bromide and L-cysteine. According to statistically analysis of orthogonal experiment results and test of significance level of each factor,optimum condition for the reaction were obtained,which were as follows: reaction time 2.5h,temperature 45℃,1:1 material molar ratio of benzyl bromide and L-cysteine.

Comparative study between composites of these two categories is made using students t-test of significance.

Comparative study is made using Students t-test of significance.

It is, moreover, possible to devise a test of significance for this measure so that one can test whether a predicted assignment is significantly different from what one, might have observed on the basis of chance observation.

Information about the use of various treatment methods was correlated with sociodemographic characteristics, and the chi-square test of significance was applied to selective findings.

Such a function provides a statistical test of significance.

An investigation was made in the field at Canton,Tung Shing,Fang Shang,Kwangtung from 1957 to 1958 to determine the degree of accuracy of threemethods for sampling the populations of plants injured by rice stem borers.It was found that under the conditions of the different densities of cultivatedplants,different degrees of insect damage,and different species of rice stemborers,the results obtained with the parallel line sampling method appeared tobe more accurate than with other two methods.Test of significance...

An investigation was made in the field at Canton,Tung Shing,Fang Shang,Kwangtung from 1957 to 1958 to determine the degree of accuracy of threemethods for sampling the populations of plants injured by rice stem borers.It was found that under the conditions of the different densities of cultivatedplants,different degrees of insect damage,and different species of rice stemborers,the results obtained with the parallel line sampling method appeared tobe more accurate than with other two methods.Test of significance of thesedata,the average of value was 0.6639.Statistical examination also showed thattwo hundred samples per field gave sufficiently high degree of accuracy.

Percentage is one of the most common indices employed in medical research. It is not desirable to apply the general formulas for the test of significance of the difference between two pro-portions, p_1-p_2, when p_1(or q_1)=0 and N_p(or N_q)<10 implying n_1 p_1(or n_1 q_1)<5, where N is the sum of the individuals of the samples, i.e.N=n_1+n_2, and p=(n_1 p_1+n_2 P_2)/N.A problem arises, here in this paper: If there is a random sample N from a population, of which r individuals have the characteristic A,when...

Percentage is one of the most common indices employed in medical research. It is not desirable to apply the general formulas for the test of significance of the difference between two pro-portions, p_1-p_2, when p_1(or q_1)=0 and N_p(or N_q)<10 implying n_1 p_1(or n_1 q_1)<5, where N is the sum of the individuals of the samples, i.e.N=n_1+n_2, and p=(n_1 p_1+n_2 P_2)/N.A problem arises, here in this paper: If there is a random sample N from a population, of which r individuals have the characteristic A,when a subsample f is drawn from the N indi-viduals, what is the probability of the event for all the r individuals possessing A to happen to fall into the subsample f? For N individuals taken r at a time, the number of all the possible combinations is (); and for f individuals ta-ken r at a time, the number of all the possible combinations is ( ). Thus, the probability of the event that all the r individuals possessing A happen to fall into the subsample f is P= (Ⅰ)or P=(Ⅱ)When both N and f are large, the following sim-plified formula can be used: P≤()~r (III) Practically, when r<10 and f>10r, the value of(f/N)~r is very close to the exact value of P.This value of P is of one tail, that is to say,the 5% level of significance used for a two-tail test will be 0.025, if these formulas are emp-loyed.Ex. 1. N=100, f=23, r=2.According to (III),P<(23/100)~2=0.053.Since f=23 is larger than 10r=20, we can esti-mate that the exact value of P is very close to 0.053, in other words, that P is larger than 0.025. By (II) we know exactly P=0.051>0.025.If the general formula, T=(p_1-p_2)/), was applied, the value of P (two-tail)would be lower than 0.01, a misleading result. Ex. 2, N=250, f=140, r=8.According to (III),P<(140/250)~8=(0.56)~8.The value of n~r can be easily found in the Bar-low's Table. Thus, we get P<0.0097<0.025.When f is less than 10r, the exact value of P can be found easily according to (I) by using the table of logarithms of binomial coefficient,1g(), and the table of logarithms or antilog-arithms.Thus, this method is the simplest and also reliable one for the test of significance between a small percentage and 0%. Notwithstanding that such a problem may also be treated other-

A spatial pattern for aphid population during the cotton seedling stage is in agreement with the negative binomial distribution when the percentage of cotton plants infested by the cotton aphid (Aphis gossypii Glover) is less than 5% and it conforms with the Polya-Eggenberger''s contagious distribution when the rate of infestation reached more than 5%. In view of this, we chose the effective period for chemical control at the stage of 20% of infestation.Since there were some difficulties arising from nonnormality...

A spatial pattern for aphid population during the cotton seedling stage is in agreement with the negative binomial distribution when the percentage of cotton plants infested by the cotton aphid (Aphis gossypii Glover) is less than 5% and it conforms with the Polya-Eggenberger''s contagious distribution when the rate of infestation reached more than 5%. In view of this, we chose the effective period for chemical control at the stage of 20% of infestation.Since there were some difficulties arising from nonnormality of error distribution, unequality of the group variance, and or non-additivity of the various effects, and since the original survey data from this investigation on aphid control were not satisfied with the assumptions for the analysis of variance, they must be transformed logarithmically into new values. This normalizing transformation will improve the accuracy of the test. The logarithmic transformation not only accommodates the experience in agricultural and biological experiments, but also conforms with the three basic assumptions underlying the analysis of variance procedure and the related tests of significance. The three basic assumptions are: (1) the experimental error should be normally distributed, (2) all the treatment groups must have the same error variance; and (3) treatment and environmental effects ought to be additive.When the sequential analysis is used to test the right time for controlling aphids, we suggest to give k=0.4, kp1=0.2 kp0=0.1, α=β=0.05, and to formulate two parallel linear equations for acceptance (am=0.143m - 5.7625) and rejection (rm = 0.143m + 5.7625) in carrying out the control measures. Because of its useful saving of labour and materials, these two equations are referable for practical application.