- Focused investigation: is to collect initial documents on the most important part of the whole. The most important part is usually the part that accounts for a large proportion of the whole research.
The results of the survey help us to perceive the basic situation of the research phenomenon but cannot be used to calculate general characteristics of the whole.
For example: investigating specialized agricultural areas such as: tea in Thai Nguyen, Ha Giang, Lam Dong, coffee in Dak Lak, etc.
- Thematic investigation: is to collect initial documents on a very small number, or even just one unit of the overall research, but to study in detail many different aspects of that unit.
The results of the investigation are not to be generalized or used as a basis for assessing the basic situation of the entire research phenomenon.
For example, investigate advanced or outdated examples.
2.1.3. Statistical investigation methods
a) Direct method: is a method of collecting initial documents in which the investigator must directly contact the investigated unit, directly conduct or supervise the weighing, measuring, counting and record documents on the investigation form.
For example: inventory survey, rice productivity survey, labor productivity survey... The direct method is mainly implemented in the following forms: direct registration
direct interview, face-to-face interview, telephone interview.
- Advantage: the original documents collected have high accuracy.
- Disadvantages:
+ Requires a lot of talent.
+ The scope of application is limited because there are many phenomena that do not allow direct observation.
b) Indirect method: is the method of collecting documents through written documents of the investigation unit, by phone or through available documents, books and papers.
For example: Survey of local births and deaths in the year, survey of family budget, etc.
The indirect method is mainly implemented in the following forms: self-registration, declaration and reporting according to the requirements stated in the survey form or statistical form sent by post to the survey unit.
- Advantages: document collection is inexpensive.
- Disadvantage: the quality of the documents is often not high.
2.1.4. Forms of statistical investigation organization
a) Periodic statistical reports
Concept: Periodic statistical reporting is a form of organizing statistical investigations on a regular and periodic basis, according to the content, methods and reporting regime uniformly prescribed by the State.
For example, every month, quarter, and year, state-owned enterprises and state-managed agencies must prepare and submit statistical reports to superior agencies and relevant agencies.
Scope of application: mainly for State-owned enterprises and State agencies
water.
Main contents of periodic statistical reports:
- Initial recording: is the first recording of the situation of the total unit.
may need investigation.
The initial records are the basis for synthesizing and calculating indicators in the Periodic Statistical Report form to regularly manage the unit's activities.
For example, in a manufacturing enterprise, it is necessary to record daily the number of workers present, the number of raw materials used, the number of products produced, etc.
- The system of indicators in periodic statistical reports: is a set of indicators that can reflect the most important aspects, properties, basic relationships between aspects of the whole and the relationship of the whole with related phenomena.
For example:
+ For production units: its basic indicators are labor and wages, costs, income and profits, etc.
+ For sectors in the national economy: its basic indicators are population and labor resources, production value, gross domestic product (GDP), consumption and living standards of the population, etc.
Effects of Periodic Statistical Reports:
+ The system of indicators has the effect of quantifying the most important aspects, objective structure, and basic relationships of the research object.
+ Is the premise for perceiving the nature, regularity and development trend of the phenomenon.
b) Professional investigation
Concept: Specialized investigation is a form of irregular investigation conducted according to a plan and method specified for each investigation.
For example : population census, customer survey, etc.
Subjects of professional investigation: are phenomena that periodic statistical reports have not or cannot regularly reflect.
For example: natural disaster investigation, work accident investigation, etc.
2.2. Statistical summary
2.2.1. Concept, meaning and tasks of statistical synthesis
a) Concept: Statistical synthesis is the scientific concentration, editing and systematization of documents collected in the investigation.
b) Significance of statistical synthesis: correct and scientific statistical synthesis is a solid basis for statistical analysis and prediction.
c) The task of statistical synthesis: to convert the individual characteristics of each aggregate unit into the common characteristics of the entire aggregate.
For example: after conducting a population census on: age, gender, occupation, etc. Through synthesizing the above survey results, statistics will present a number of synthetic indicators reflecting the characteristics of the entire population of our country such as: size, structure, population distribution, labor resources, etc.
The purpose of statistical synthesis is to generalize the general characteristics of the research population using statistical indicators. The results of statistical synthesis are the basis for statistical analysis.
2.2.2. Statistical grouping
2.2.2.1. Concept, meaning and tasks of statistical grouping
a) Concept
Statistical grouping is based on one or several criteria to divide units in the whole into groups, sub-groups, and sub-groups with different characteristics to meet the purpose and requirements of the research.
For example: population disaggregation by gender, working age, school age, etc. Statistical disaggregation includes the following types:
- Based on the number of criteria used:
+ Simple grouping: is grouping according to one criterion.
For example: Population grouping by gender, industrial enterprises grouping by number of workers...
+ Complex grouping: is grouping according to many criteria.
For example: Disaggregate population by gender, working age, class composition, ethnicity, etc.
- Based on the nature of the statistical classification criteria:
+ Grouping by attribute criteria: is based on criteria that cannot be directly expressed by specific numbers to perform grouping.
For example: Classify industrial enterprises according to economic sector criteria such as: Private enterprises, LLCs, Joint Stock Companies, etc.
+ Grouping by quantity criteria: is based on criteria that can be directly expressed by specific numbers to carry out grouping.
For example: Group retail stores in the commercial sector according to the following criteria: number of sales staff, sales volume, sales revenue, etc. - Based on the distance between groups:
+ Grouping without group spacing: is grouping in which each group has only one limit of discontinuous variables.
For example: Grouping households by number of children, grouping student classes by age, etc.
+ Grouping with group spacing: is a grouping in which each group has two variable limits, called the lower limit and the upper limit of the group.
For example: Classify a type of fruit by weight, classify workers by productivity level, etc.
b) Meaning of statistical grouping
- Statistical disaggregation is the only basic method used to synthesize statistical survey data.
- Documents on statistical disaggregation results are the basis for calculating statistical analysis indicators - performing the statistical analysis phase.
- Through the results of statistical disaggregation, we obtain aggregated data by subgroup, group, group of groups and the whole, which can give us preliminary comments, comparisons between subgroups, groups of groups, showing the important position of each subgroup, group, group of groups in the overall research phenomenon.
c) Tasks of statistical division
The task of statistical analysis is to perform the task of statistical synthesis: to edit, arrange, classify and systematize the collected statistical survey documents to obtain total and aggregate data to serve the analysis requirements of structure, of the relationship between units in the whole, between research criteria of the phenomenon.
2.2.2.2. Determine the grouping criteria
The grouping criterion is the criterion chosen as the basis for statistical grouping. When researching a certain topic in a socio-economic phenomenon,
The socio-economic phenomenon itself has a number of characteristics that can be considered as statistical classification criteria.
For example: When researching the topic of classifying industrial manufacturing enterprises by size, it can be expressed on a number of specific criteria such as: product output value, quantity of each main product type, number of production workers, value of production machinery and equipment, etc.
Each criterion has different meanings and important roles in statistical grouping under certain specific conditions.
Accurate and scientific grouping first depends on the choice of grouping criteria.
To ensure the selection of the classification criteria is accurate and reflects the true nature of the phenomenon, the following principles can be used:
- Based on a deep and correct theoretical analysis of the nature of the research phenomenon according to the research purpose and requirements.
For example:
+ The nature of the enterprise's production method is advanced modern technology, so the study classifies the enterprise's scale according to the criteria of value of machinery and equipment, costs, and modern production techniques.
+ The nature of the production method of the enterprise is mainly manual (based on human labor), so the study of the scale of the enterprise is based on the criterion of the number of workers.
- Based on the specific historical conditions of the development stages of the research phenomenon, analyze deeply and choose appropriate essential criteria to meet the analysis requirements at each specific stage.
For example: Analyzing the lives of farmers in Northern Vietnam before the August Revolution in 1945, it is necessary to deeply analyze the criteria of land ownership, etc.
2.2.2.2. Determine the number of groups needed
a) Grouping by attribute criteria:
In this clustering, the number of clusters is equal to the number of different types of the research phenomenon. There are two cases:
- If the number of types is relatively small, each type can be considered a group.
For example : Disaggregate population by gender, disaggregate enterprises by economic sector.
economy,…
If the number of types of phenomena is large, the number of groups is very large. These cases
In this case, the State usually makes a list.
For example : List of goods, list of occupations, list of national economic sectors, etc.
b) Grouping by quantity criterion: there are 2 cases
- In case of grouping without group distance: applied when the number of variables changes little, meaning the difference in quantity between units is not much such as: number of people in a family, number of machines operated by a worker, etc., then the number of groups is formed by the number of variables.
For example: Disaggregate the number of households in a locality according to the number of children in each family to study the economic life of the families.
- In case of grouping with group distance: applied when the variable quantity of this criterion changes greatly. If each variable quantity forms a group, the number of groups will be too large, and at the same time, the qualitative difference between the groups will not be clearly stated. In this case, it is necessary to pay attention to the relationship between the quantity and quality of the phenomenon. There are 2 cases:
+ Equal group spacing: applied when the fluctuation phenomenon is relatively even. The value of equal group spacing is determined as follows:
For continuous variables: the upper limit of the previous set coincides with the lower limit of the next set.
Xmax - Xmin | |
d = | |
n | |
In there : | |
d | : The value of the nest distance |
Xmax | : The largest variable of the criterion |
Xmin | : The smallest variable of the criterion |
n | : Number of groups |
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For example: Determine the group distance of the sales grouping criterion of the trade industry in the research year with the data: the largest variable in sales is 1,200 billion VND and the smallest variable in sales is 300 billion VND. The number of groups planned to be divided is 6 groups.
Requirement: The groups must be evenly spaced and the limit of the previous group must coincide with the limit of the next group.
- For discrete variables: the lower limit of the next group is greater than the upper limit of the previous group.
d = |
n |
+ Uneven nest spacing: applied when the phenomenon of uneven fluctuations makes the different properties between nests uneven and depends on the research purpose to determine whether the nest spacing is even or uneven.
For example: Population breakdown in a locality in 2019 by age is as follows:
Age
Population (thousand people) | Note | ||
- Under 1 year old | 120 | Still breastfeeding | |
-From 1 | - 3 years old | 280 | Nursery |
-From 4 | - 6 years old | 470 | Kindergarten |
-From 7 | - 18 years old | 650 | High school |
- From 19 - 60 years old | 1,200 | Working age | |
- 61 years of age or older | 350 | Retirement age | |
Add | 3,100 | ||
Attention :
Discrete variables : are variables that we can count and count accurately (expressed as integers).
For example: number of employees, number of workers, number of products, etc.
Continuous variables : are variables that we cannot count (expressed in decimal numbers).
For example: labor productivity, average height, production value, production cost, product price, etc.
2.2.2.4. Determine explanatory indicators
a) Concept : Explanatory indicators are indicators used to explain the specific characteristics of each group and the whole.
b) Effect of explanatory indicators:
- Helps us clearly see the quantitative characteristics of each group and of the whole, as a basis for comparing groups with each other and for calculating a series of other analytical indicators.
- To determine the explanatory indicators, it is necessary to base on the research purpose and the main task of the subgroup to select indicators that are related and complementary to each other.
- Explanatory indicators should be arranged in a logical order to facilitate comparison and perception of phenomena. Indicators that are important in comparison should be arranged close together.
2.3. Organization of statistical synthesis
2.3.1. Form of statistical synthesis organization
a) Contents of statistical synthesis: Based on one of the criteria identified during the investigation phase.
Organization and statistical synthesis techniques: there are 2 forms: level-wise synthesis and centralized synthesis.
- Synthesis at each level: is the organization of synthesizing investigation documents step by step, level by level from bottom to top according to a pre-planned plan.
- Centralized synthesis : all original documents are centralized in one agency to be edited and systematized from beginning to end.
Synthesis techniques can be divided into two types: manual synthesis and machine synthesis.
b) Prepare and check documents used for synthesis:
- Must gather enough survey forms or other documents to be able to meet the assigned tasks.
- The inspection aims to ensure the accuracy of the initial investigation documents, serving the correct calculation of later analysis indicators.
2.3.2. Statistical synthesis techniques
- Manual synthesis: applied in cases where the volume of documents is not large and the content is simple.
- Manual synthesis: applied in cases of large volumes of documents and complex content.
Statistical summary results are presented in statistical tables or statistical graphs.
2.4. Statistical tables and statistical graphs
2.4.1. Statistical table: is a form of presenting statistical documents in a systematic, reasonable and clear manner to express the quantitative characteristics of the phenomenon.
2.4.1.1. Components of a statistical table
a) In terms of form: The statistical table includes horizontal rows and vertical columns, titles and figures.
- Horizontal rows and vertical columns: reflect the scale of the table.
- Title: reflects the content of the table and of each detail in the table.
- Data: are recorded in the cells of the table, each number reflects a quantitative characteristic of the research phenomenon.
b) About content:
- Topic section: presents the overall phenomenon presented in the statistical table. The topic section is usually placed on the left side of the table.
- Explanation section: includes indicators explaining the characteristics of the research object (explaining the topic part of the table). The explanation section is usually at the top of the table.
Composition of the statistical table:
Table name (general title)
Explanation
Topic section
Explanatory indicators (Column name) | Total | |||||
1 | 2 | 3 | … | n | ||
Topic Name (product name) | ||||||
…. | ||||||
Total | ||||||