Running Header Finance

Question: Discuss about the Running Header for Finance. Answer: Level of significance are 90%, 95%, 99% Type I error Data analysis Deviation and spread P value Null Alternative hypothesis; Null hypothesis It means that there is substantial evidence against the null hypothesis and we reject it at 5% Age, sex, income, occupation It is used to emphasize that the data mining or finding data to prove a hypothesis but it does not mean that observational data is enough to infer the causation. To prove the hypothesis one must have experimental data which can lead to infer the causation. a Data Integration: collect data from all the different sources. b Data selection: Select the data which will be useful for mining c Data Cleaning: Remove the error in the data selected d Data Extraction: Extracting relevant information from the data e Data Interpretation: Interpreting the results obtained. a Clustering b Regression c Decision trees d Neural network e Genetic Algorithm Data Mining Data Mining Big data Randomized response Correlation regression Selection Selection Interview and survey The data selected can serve the purpose for which it is selected A representative sample is a small amount which represents the characteristics of the larger entity accurately. The researcher can avoid bias by Doing a preliminary research and asking open ended questions Clearly outlining the population for which the study is to be conducted The researcher should have complete understanding of all the statistical techniques before starting the research. The consequence of improperly collected data are The researcher will not be able to answer research questions inaccurately. The researcher will not be able to repeat and the validate the study The researcher will lose trust and will not be consulted for further studies. Data selection is dependent on purpose for which data will be used, potential reuse, timeframe for which the data will be used, budget for data selection. References Data Mining. (n.d.). Retrieved from https://dataminingwarehousing.blogspot.in/2008/10/data-mining-steps-of-data-mining.html Representative Sample. (n.d.). Retrieved from https://www.investopedia.com/terms/r/representative-sample.asp https://fluidsurveys.com/university/tips-for-overcoming-researcher-bias/ Tips for Overcoming Researcher Bias. (2013) . Retrieved from https://fluidsurveys.com/university/tips-for-overcoming-researcher-bias/ Five steps to decide what data to keep. (n.d.). Retrieved from https://www.dcc.ac.uk/resources/how-guides/five-steps-decide-what-data-keep