1. Statistics : data collection and processing analysis and interpretation of data and draw conclusions from scientific data from all areas of
the collection: that is to obtain statistical data
processing: the data presentation in the form of charts out
analysis: appropriate statistical methods to research data selection , and extract useful information from the obtained data further concluded
2. data analysis methods : method 1 Descriptive statistics: data collection, processing, aggregation, graphically depicts, summaries and analyzes statistical method
2. the inferential statistics methods: how to use the sample data to infer the general characteristics of statistical methods
such as: analysis of demographic characteristics, product quality inspection
3. The real purpose of the analysis of data : data to find out from the law, inspired from the data set, rather than looking for support
true data analysis without prior conclusion by analyzing the data in order to draw conclusions
4. Statistical data type ( distinguishing data type important, different statistical data to take a different approach to processing and analysis ):
1. classification data: male, female; business is divided into appliances, pharmaceutical companies, furniture (qualitative + quality / data)
2. the order of the data: seasons ; pass in good excellent; strongly agree, agree, neutral, disagree (+ qualitative quality / data)
3. numerical data: measured according to the scale number of observations, the results are expressed as specific numerical values (in reality such a basic processing data) (quantitative number + / data)
Sectional data : the same space at different times ---> 2010 GDP of each province region
time-series data : the same space at different times ---> 2010--2019 China's GDP data
5. Statistical basic concepts :
5.1 Overall : a collection of all of the individual (data) included research by the individual studies of the composition
determine the overall scope of the sometimes easy and sometimes difficult: the lamp life; whether consumers like to drink (difficult to determine consumer groups)
the overall number of units can be divided into: limited individual (independent) and unlimited individual (not independent)
overall statistics on usually is a set of observed data rather than a group of people or some of the items
5.2 sample : from population extracting a portion of the set of elements, the number of constituent elements of a sample becomes sample
Objective: the sample is determined to provide the overall feature information (100 samples extracted from the bulb with the 100 samples to the average life of the lamp is determined)
5.3 Parameters : used to describe the general features of the general population is a digital measure of a certain characteristic value of the researcher wants to learn (population mean (mu), standard deviation (sigma), the overall ratio (PI))
unknown parameter according to certain values of the samples is calculated to estimate the parameter by
5.4 statistics : used to describe the general characteristics of the digital measurement sample (sample average (x-bar), the sample standard deviation (s), the sample proportion (p))
it is based on a quantity of sample data calculated result of random sampling is thus a function of sample statistics
to estimate the parameter [x-bar ---> the sample statistics u, s ---> sigma, p ---> pi ]
three above processing statistics, statistical analysis needs to constructed the statistic: Z statistic, t statistic, X ^ 2 statistic, F statistic
6. variables : the concept described phenomenon certain characteristic , which is characterized by from one to the next observation observations showing a difference or change (merchandise sales, education, quality grade products)
Variable value ----->
1. Categorical variables: Description of a category of things ----> disaggregated data: gender - male, female; business - electronics, pharmaceutical companies, automobile
2. order argument: Explanation names of things ordered a category ---> order data: four seasons - seasons; product grade - first-class product, second product, third-class products
3. numeric variables: Description digital characteristics of things a name -----> numeric data: product output, sales , age, time
3.1: discrete variables - can only take the value it can only be a finite number of values, the value of the whole was off-digit enumerate (the number of enterprises, product number)
3.2: continuous variables - can variable interval take on any value in one or more of the value of continuous can not list them (age, temperature, error)
in the face of social and economic problems when the study of discrete variable values can be a lot of time when discrete variables treated as continuous variables