statistics homework answers

statistics homework answers

The Importance of Statistics in Decision Making

1. Introduction to Statistics

Statistics is a critical process that entails learning and computation that will enable a researcher to make a prediction based on inference. Not only is it a tool for prediction but it is also used for evaluating the obtained results from the data, and for testing the difference between two given processes. Another important aspect of statistics is that the idea of one data process is regarded as an instance. This notion has an inherent probability that any given result will occur. When more data is obtained for any process, the result of the data will typically change. This change is due to sampling error. So, another aspect of statistics is to infer a given data set. This means that a researcher will attempt to answer a given question about the process in an environment with uncertainty.

The term “statistics” has several meanings. However, it is used to refer to the actual data or to a quantitative description of a set of data. It is a tool for creating an understanding from a set of numbers. It can also be used to compare two sets of data, or to make an inference or a prediction about a population based on a sample of data. An example of making a prediction is when a retail store has a certain sample of numerical data from their past customers. They can use that data to determine what the expectations for the future customers might be.

2. Basic Concepts in Statistics

ii) Secondary Data: When the data are collected from a source which already has the data in an organized manner (like library, internet etc), it is called the Secondary Data. This type of data is easier and cheaper to obtain but may not be reliable and accurate as it was not collected specifically to solve the problem at hand. This type of data can save time and effort, particularly in a feasibility study. E.g. Census data, Time-use surveys etc.

i) Primary Data: When the data are collected for the first time by the investigator or his agent (from government report, Annual Reports of a Company, Research reports etc), it is called Primary Data. This type of data is generally more reliable and accurate, but is more expensive and difficult to obtain. E.g. Questionnaire method, Observation method etc.

Before we go to the further details, it is necessary to know about the statistics and its applications. The word ‘Statistics’ has been derived from Latin word ‘Status’ means a ‘Political State’. Statistics makes use of the term Data. Data can be anything like any information about any thing going on in the environment. The Data can be of two types:

3. Statistical Analysis Techniques

Statistical analysis techniques. This study importance includes a descriptive introduction to statistics and the choice of data and elementary probability. We then move into probability distributions and from there we develop into inferential statistics. This study utilizes both the paper and PowerPoint presentation. This study is a valuable tool for learning statistics and probability and is a fundamental component of any statistics class. It was also useful to learn to use and apply various different statistical analysis techniques using Minitab and Microsoft Excel, which is the software of choice in the real world. Starting from kernel density functions to various probability distributions, I have gained knowledge on how different types of data sets can be analyzed and interpreted in many different ways. This has been a valuable experience as it has provided me with a platform to generate new methods of investigation and analysis in search for the correct method in best answering the question at hand. Through conducting various different analysis interpretations and assessing, it is then conveyed in a meaningful manner where we have acquired knowledge on ways to best communicate the elements and findings of analysis work so as to facilitate clear understanding. This has been achieved by further exploring into written and oral presentation and the use of data visualization. The wide array of knowledge we have acquired in this study is highly useful for anyone in the field of mathematics or statistics. Overall, this study has been enjoyable, rewarding, and more importantly has provided me with a stronger foundation and greater confidence in probability and statistics.

4. Application of Statistics in Real Life

Statistics can offer no resolution to these economic problems, but there is certainly a proper way to apply this data. The Chamberlain company, a health and food natural ingredient supplier, recently used a statistical study to determine if changing the price for shipping their product would affect their bottom line. In a case study performed by an outside statistician, they were asked to alter the price of shipping by an increment of $5. They had the statistician analyze the shipping data in comparison to a time of good economic growth, and compared the impact of what the increase in shipping would do during hard times. The regression analysis could not predict the future price elasticity, but gave enough evidence to show that there would be little adverse effect to the changes. The fact that people still need to eat and live healthy did show in the sales data. The study of data in comparison to past data and future predictions can be very useful in a business trying to continue normal operations in an economically tough time.

Creating a plan of action is so important in so many areas of life. It is certainly vital to make business decisions, but it may also be necessary to make personal decisions based on statistical data. Everyone in this country is exposed to economic statistics on an almost daily basis through one medium or another. In the last twelve months, consumers have been beaten over the head with evidence about how the economy has affected their lives. We’ve seen and read countless news stories about how the Great Recession has changed the way people spend their money. High-end retailers are closing their doors as their customers turn to discount stores, trading down from name brand products to private label, and luxuries turn into necessities. The popularity of generic brands is soaring, since 2008 there has been a 14% growth in the sale of generic products. With these changing behaviors, businesses are continuing to find ways to cut costs and jobs. The US has lost over 3 million jobs since December 2007, and the measure of job losses has been getting smaller each month. In September of 2010, unemployment rates were at 9.6%, roughly the same percentage as the previous two months. This is a great deal of statistical data, but what can it tell us and what decisions can be made?

5. Conclusion

We do not mean what we say or say what we mean, unless we are totally objective about our purpose and meaning. There is constant misunderstanding and no communication between individual purchasers of stock in the Stock Exchange because they do not share mutually the same beliefs about the future. While the public is convinced that democracy is the echo of its wishes, it is nonetheless a matter of faith for the minority who direct national policy. All questions of public policy and many questions of business are questions of what men are thinking about other men; where truth is remote and the beliefs are changeable, statistics are the only logic. Probability is perhaps the most systematic and logical attempts on the part of the mind to grapple with uncertainty. The science of drawing useful inferences from data is statistics, and its methodology rests on the same universal intellectual implementation which is used for the aforesaid purpose. In everyday decision making, there is seldom a decision which does not have to be based on speculation or prediction, i.e. there are no unfailing facts for such decisions. To decide what is best to we now for some expected future, or to find the best way of applying our resources and effort in order to achieve a desired objective in the future are typical problems of planning. The range of our predictions may encompass immediate or extremely remote future and the decisions which it concerns vary from routine matters to those which are unstructured and uncertain. Decision can be seen as a course of action which is followed by an outcome. Given the decision and the range of alternative outcomes, we may be able to identify the best result i.e. the one which is optimal in some sense or usually decision making is done in the belief of achieving a desired result. At the heart of a logical approach to decision making in an inference concerning the given course of action and the best choice of decision is simply the choice between alternative actions. It is here that the relevance of statistics to decision making is most apparent, since statistics is the science of drawing inference from data, it is most often the case that a decision is essentially a choice of one action or plan, followed by an attempt to assess its probably relative to other actions and contingent results. An optimal decision can be based only on a comparison of the known or conjectured effects of the various different actions. The quality of the decision involves the choice of the best action, is assessed in terms of its effectiveness, to the finding the best decision and its effectiveness, to the finding the best course of action, its relative to utilizing given resources often provides the topic of plan and evaluation of many decision. Step an act which will change the future course in two alternative states an action probability of better result, can all be viewed as a specially the comparison of the various decisions. Here the entire theoretical constructs of statistics is useful and most decision problems will be as complex if not more so, than the example in statistics texts. An inference aka decision is premiere results failure view and the ability to make right decisions alter previous bad one, provide another chance, is exactly the error and testing concept in testing hypothesis and in statistics, the resort to redecision change and marginal an alternate ways are all comparisons with the trying different and contrasting actions with it faint hopes some for new information and possible learning to change old decision. The sheer logic of statistics makes it a fix science a find the trip best way that it common the most help decision makers is a different matter.