Statistics for Bi - Hypothesis Testing
Statistics for Business Intelligence – Hypothesis Testing
Index:
1. What is Hypothesis testing in Business Intelligence terms? 2. Define - “Statistical Hypothesis Testing” – “Inferences in Business” – and “Predictive Analysis” 3. Importance of Hypothesis Testing in Business with Examples 4. Statistical Methods to perform Hypothesis Testing in Business Intelligence 5. Identify Statistical variables required to compute Hypothesis testing. a. Correlate computing those variables from the data available in normalized tables arranged in row x columns. 6. Computing Statistical Hypothesis Testing for Business Decisions using Algorithms 7. User Interface Development for Presentation of Hypothesis feature 8. How does it fit in Prajna?
1. What is Hypothesis testing in Business Intelligence?
Hypothesis Testing – is used to prove or disprove the research (Business proposed decision) hypothesis by providing more measurable or concrete hypothesis statement. for example, a research hypothesis could be that the stock market index reflects the state of monsoon in the country. A statistical hypothesis might look at the values of the index with the percentage increase or decrease in rainfall during the year compared to previous years. Hypothesis Testing is a study about * How to test a sample against a benchmark? * How to assess the risk of incorrect decisions?
Identifying the confidence intervals for a decision-required item does these.
2. Statistical Hypothesis Testing – Inferences drawn in Business – and Predictive Analysis made for Business
Inferences – Inferential statistics is the term given to the branch of statistics that uses the information from the sample to infer the information about the population. For example, given a sample mean , the population mean (also called a parameter) can be determined using inferential statistics.
Statistical Hypothesis – A statistical hypothesis test is a method
Index:
1. What is Hypothesis testing in Business Intelligence terms? 2. Define - “Statistical Hypothesis Testing” – “Inferences in Business” – and “Predictive Analysis” 3. Importance of Hypothesis Testing in Business with Examples 4. Statistical Methods to perform Hypothesis Testing in Business Intelligence 5. Identify Statistical variables required to compute Hypothesis testing. a. Correlate computing those variables from the data available in normalized tables arranged in row x columns. 6. Computing Statistical Hypothesis Testing for Business Decisions using Algorithms 7. User Interface Development for Presentation of Hypothesis feature 8. How does it fit in Prajna?
1. What is Hypothesis testing in Business Intelligence?
Hypothesis Testing – is used to prove or disprove the research (Business proposed decision) hypothesis by providing more measurable or concrete hypothesis statement. for example, a research hypothesis could be that the stock market index reflects the state of monsoon in the country. A statistical hypothesis might look at the values of the index with the percentage increase or decrease in rainfall during the year compared to previous years. Hypothesis Testing is a study about * How to test a sample against a benchmark? * How to assess the risk of incorrect decisions?
Identifying the confidence intervals for a decision-required item does these.
2. Statistical Hypothesis Testing – Inferences drawn in Business – and Predictive Analysis made for Business
Inferences – Inferential statistics is the term given to the branch of statistics that uses the information from the sample to infer the information about the population. For example, given a sample mean , the population mean (also called a parameter) can be determined using inferential statistics.
Statistical Hypothesis – A statistical hypothesis test is a method
References: – Content Presented above is extracted from net and from Statistics in Business Intelligence Books. To my knowledge I tried to list all web links from which I pulled content to phrase this Idea Submission. 1. http://en.wikipedia.org/ 2. http://www.dictionary.com 3. http://mithil-tech.blogspot.in/2009/08/statistics-for-business-intelligence_10.html 4. Book: Applied Statistics in Business and Economics David P. Doane and Lori E. Seward