In order to obtain a piece of information, what should be considered in order to analyze it statisti

The first is the authenticity and practical significance of the data, if it is not necessary, there is no need for further analysis, because if the conclusion is already standing on the unrealistic cornerstone, it is to talk nonsense with yourself and be tired and panicked.

Secondly, if the way and method of data collection are reasonable, then whether the collected data is sufficient, whether it is enough to export the results, is also a very important step, if the data is not enough on the basis of their own to export the desired results, then it will take some weeks.

If you want to get multi-level results, you have to try to analyze this batch of data from multiple angles, but there is foreshadowing at the time of data collection in advance, and if not, you have to connect the general environment to attack.

Since your question is very general, I can only make general generalities.

If you have limited knowledge and insight, you can only believe it selectively, and if you don't want to suffer a loss, don't touch anything. If you want to gain something from it, you can collect information again in its scope and surrounding areas, or ask people in the industry to analyze, and it is best for these people to be far away from the source of interests.

The analysis of general content can be roughly divided into the following aspects:

Macro (the general environment, the overall trend, their own position, comparison with the same industry).

micro (problems with internal structure and organizational management arrangements, own strengths and weaknesses).

onlookers (and the interrelationship of the surroundings).

The credibility of the results of the analysis is related to the personal presentation ability and presentation method of the presenter. This varies from person to person, and can only be silently blessed ...... again

The key is what your purpose is, what you have to use statistics to illustrate, and figure this out before you go to statistics. And what data is originally on your profile, which determines what you can count. If you want to know the principles and processes of statistics, it may be helpful to read Statistics.

What are the main methods of statistical analysis? What role do these methods play in data analysis?

Hello, glad to answer for you, method.

First, the index burning Huai hand comparative analysis method. It is also known as the comparative disadvantage analysis method, which is the most commonly used method in statistical analysis. It is a method that reflects the differences and changes in the number of things through the comparison of targeted indicators. Method.

2. Group analysis. The index comparison analysis method is a comparison of the whole, but the units that make up the statistical population have a variety of characteristics, which makes many differences between the units within the same population, and the statistical analysis should not only analyze the quantitative characteristics of the population and the quantitative sapience.

1) Frequency distribution.

2) Mean and standard early branch deficit differences.

3) Correlation analysis.

4) Regression analysis is a scientific method to make the best of unknown phenomena according to known phenomena.

5) Cluster analysis is to classify individuals according to their characteristics, so that individuals within the same category have the highest degree of homogeneity, and the highest degree of heterogeneity between the categories. Especially when segmenting consumers, we often use the method of cluster analysis.

6) Factor analysis is a multivariate simplification technique that aims to decompose the original variables and derive potential "categories" from them.

7) Joint analysis is a method of evaluating consumer preferences, which uses the method of decomposition, that is, asking consumers to assign values to a series of product profiles, and using these assignments to calculate preference parameters. These parameters can be scores, weights, ideal points, and so on.

Answer]: Correct statistical comprehensive analysis is based on statistical data, starting from the number of phenomena, analyzing and researching the relationship between the number of social and economic phenomena, so as to clarify the Zen and put forward questions and suggestions.

What are the main methods of statistical analysis? What are the roles of these methods in data analysis?

Hello, dear, I am glad to answer for you: what are the main methods of data statistical analysis? What are the roles of these methods in data analysis?

A The statistical analysis methods are as follows: 1. Descriptive StatisticsDescriptive statistics is the use of charts or mathematics to organize and analyze data and information, and to estimate and describe the relationships between data distributions, numerical features, and random variables.

The description is divided into three sections: Focused Trend Analysis, Off-Center Trend Analysis, and Coherent Analysis. 1. Concentration Trend AnalysisConcentration trend analysis mainly relies on statistical indicators such as average, median, and mode to show the concentration trend of data.

2. Deviation from the center trend analysis is to study the importance of data deviation from the trend through statistical indicators such as total distance, quartile difference, mean difference, variance (covariance: a statistic used to measure the relationship between two random variables) and scale difference. 3. Coherent analysis: Coherent analysis: Discuss whether there is a statistical correlation between the data.

Two. Hypothesis testingA hypothesis test is a type of statistical inference that is used to determine whether differences between samples and between samples and populations are caused by sampling error or substantial differences. Hypothesis testing can be divided into three categories:

Normal distribution test, normal population mean distribution test, and non-parametric test. 1. Normal distribution testThere are three types of normal distribution test: JB test, KS test and Lilliefors test, which are used to test whether the sample comes from the positive buried distribution population.

2. Statistically speaking, the difference between the mean values of each sample should be within the allowable range of random error. On the other hand, if the difference between the mean values of different samples exceeds the allowable range, it indicates that there is a systematic error between the mean values in addition to random error, resulting in a significant difference between the mean values. 3. Non-parametric test: The non-parametric test does not consider whether the total deviation is known, and only uses some very intuitive information from the sample test value.