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inferential statistics tries to infer from the sample data what the population might think. They can use inferential statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in a study.

Business Statistics is the science of good decision making in the face of uncertainty and is used in many disciplines such as financial analysis, econometrics, auditing, production and operations including services improvement, and marketing research. These sources feature regular repetitive publication of series of data. This makes the topic of time series especially important for business statistics. It is also a branch of applied statistics working mostly on data collected as a by-product of doing business or by government agencies. It provides knowledge and skills to interpret and use statistical techniques in a variety of business applications. A typical business statistics course is intended for business majors, and covers statistical study, descriptive statistics (collection, description, analysis, and summary of data), probability, and the binomial and normal distributions, test of hypotheses and confidence intervals, linear regression, and correlation. Role of Statistics in Economic: Economic statistics is a branch of applied statistics focusing on the collection, processing, compilation and dissemination of statistics concerning the economy of a region, a country or a group of countries. Economic statistics is also referred as a subtopic of official statistics, since most of the economic statistics are produced by official organizations (e.g. statistical institutes, supranational organizations, central banks, ministries, etc.). Economic statistics provide the empirical data needed in economic research (econometrics) and they are the basis for decision and economic policy making. Econometric: Econometrics is concerned with the tasks of developing and applying quantitative or statistical methods to the study and elucidation of economic principles. Econometrics combines economic theory with statistics to analyze and test economic relationships.

Statisticians are concerned that the business world does not regard statistical literacy, or statisticians, as important. Little progress has been made in spreading the belief in the power of statistics to the non-statistical. This problem is as strong in the context of supporting organizational and product quality improvement as it is elsewhere. We summarize the effect of Genichi Taguchi's work on industrial experimentation, as well as developments in the use of statistical process control, statistical reliability requirements and other statistical approaches to quality. The effect of developments in quality systems standards, such as BS EN ISO 9000, the European Business Excellence Award Model and the Baldrige Award, are also discussed. We argue that statisticians' attitudes to non-statisticians and the use of their discipline will have to change if statistics is to realize its potential in supporting quality improvement. Re-education is necessary not just for the non-statistician but for the statistical community as well.

Statisticians are concerned that the business world does not regard statistical literacy, or statisticians, as important. Little progress has been made in spreading the belief in the power of statistics to the non-statistical. This problem is as strong in the context of supporting organizational and product quality improvement as it is elsewhere. We summarize the effect of Genichi Taguchi's work on industrial experimentation, as well as developments in the use of statistical process control, statistical reliability requirements and other statistical approaches to quality. The effect of developments in quality systems standards, such as BS EN ISO 9000, the European Business Excellence Award Model and the Baldrige Award, are also discussed. We argue that statisticians' attitudes to non-statisticians and the use of their discipline will have to change if statistics is to realize its potential in supporting quality improvement.

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Q: What is the role of inferential statistics in business?
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Related questions

What is inferential data?

There is no inferential data. There is inferential statistics which from samples, you infer or draw a conclusion about the population. Hypothesis testing is an example of inferential statistics.


Why are measures of variability essential to inferential statistics?

Why are measures of variability essential to inferential statistics?


Explain the role of inferential statistic in business?

looking for a simple expanation


When should inferential statistics typically be used?

Inferential statistics uses data from a small group to make generalizations or inferences about a larger group of people. Inferential statistics should be used with "inferences".


What are descriptive statistics and inferential statistics?

Descriptive statistics is a summary of data. Inferential statistics try to reach conclusion that extend beyond the immediate data alone.


Types of statistics?

There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.


What are the two kinds of statistics?

Descriptive and Inferential Statistics


Does inductive statistics and inferential statistics same?

yes


What are the advantages and disadvantages of inferential statistics?

One advantage of inferential statistics is that large predictions can be made from small data sets. However, if the sample is not representative of the population then the predictions will be incorrect.


Compare and contrast descriptive statistics and inferential statistics?

Descriptive statistics are meant to describe the situation such as the average or the range. Inferential statistics is used to differentiate between a couple of groups.


What are the catagories of statistics?

Descriptive and inferential


What level of measurement do most inferential statistics rely upon?

Level of measurement most inferential statistics rely upon is ratio.