Statistics Is The Science Of Collecting Data And Analyzing It

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Statistics is the science of collecting data and analyzing it in large quantities to predict or prepare outcomes based on data gathered. This paper will share with you an insight as to what I learned over the past five weeks in Business Statistics. It will include a detailed look at descriptive statistics, inferential statistics, hypothesis development and testing, selection of appropriate statistical tests, evaluating statistical results, and a close look at the role of statistics. Business statistics has changed the way managers manage, with so much information at everyone’s finger tips and with companies wanting to be more efficient, “Managers need to learn to efficiently and effectively access, filter, summarize, interpret and report…show more content…
We try to conclude from the evidence what a sample group may think. For inferential statistics, we use it to make decisions on the probability of the observed difference between the groups and if it is dependable or just happened by chance based on the group. “…we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simple to describe what’s going on in our data (socialresearchmethods.net).” An example of inferential statistics is, a gym teacher wants to know the average amount of three point shots the students in this particular school can make in 30 seconds, he chooses only the students on the basketball team to sample it, the results he get would not be a representative sample simply because that does not represent a random sample of the entire school, but the results he gets and writes from this test would be considered an inferential statistic. In quantitative research we are trying to answer a question or prove a hypothesis that we have. To do this, in statistics there is a process call hypothesis testing or otherwise known as a significance test. When doing a significance test, we must first set up our hypothesis or educated guess as to what we think the research will prove. For our example, we are going to take a coin with both a heads side and a
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