Eight common non-parameter tests in SPSS 2: Binomial Test

 

I. Definition

In real life, there are only two types of data values, such as the birth and death in medicine, the existence and absence of illness, the male and female in gender, and the conformity and inqualification of products. All possible results extracted from this binary classification population are either in the opposite category or in another category. The frequency distribution is called a binary distribution. The binary distribution test (Binomial) in SPSS can be called to analyze the sample data.

The two-item distribution test of SPSS is to infer whether the overall distribution is subject to a specified two-item distribution based on the collected sample data. The null hypothesis is H0: there is no significant difference between the population and the specified binary distribution.

In the binary distribution test in SPSS, when the number of samples is less than or equal to 30, the formula for calculating the probability of the binary distribution is calculated. When the number of samples is greater than 30, the Z statistic is calculated, under the zero hypothesis, the Z-statistic follows a normal distribution. The formula for calculating the Z statistic is as follows:

SPSS will automatically calculate the Z statistic and give the corresponding accompanied probability value. If the accompanied probability is less than or equal to the user's significance level α, the null hypothesis H0 should be rejected, and the overall distribution form of the sample from is considered to be significantly different from the specified two distributions; if the accompanied probability value is greater than the significance level, the zero hypothesis H0 cannot be rejected, and the overall distribution form of the sample from does not significantly differ from the specified two distributions.

The data of the two distribution tests of SPSS is the sample data actually collected, rather than the frequency data.

 

Ii. Instances

35 babies were born in a certain period of time in a certain place, including 19 women (fixed Sex = 0) and 16 men (fixed Sex = 1 ). Q: Is the gender ratio of a baby born in this region different from that of a normal male or female (with an overall probability of about 0.5? The data is shown in Table 10-2.

Gender of 35 infants

 

Baby	Sex	Baby	Sex	Baby	Sex
1	1	13	1	25	1
2	0	14	1	26	1
3	1	15	1	27	0
4	1	16	1	28	0
5	1	17	0	29	0
6	1	18	0	30	0
7	0	19	0	31	1
8	0	20	0	32	0
9	0	21	0	33	0
10	0	22	0	34	0
11	1	23	1	35	0
12	1	24	1

 

Test procedure:

 

1. Chi-square test: http://www.cnblogs.com/downmoon/archive/2012/03/06/2382042.html

2. Two-item distribution test: http://www.cnblogs.com/downmoon/archive/2012/03/26/2417668.html

3, travel inspection: http://www.cnblogs.com/downmoon/archive/2012/03/26/2417882.html