统计代写|商业分析作业代写Statistical Modelling for Business代考|More about Surveys and Errors in Survey

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商业分析就是利用数据分析和统计的方法,来分析企业之前的商业表现,从而通过分析结果来对未来的商业战略进行预测和指导 。

statistics-lab™ 为您的留学生涯保驾护航 在代写商业分析Statistical Modelling for Business方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写商业分析Statistical Modelling for Business方面经验极为丰富,各种代写商业分析Statistical Modelling for Business相关的作业也就用不着说。

我们提供的商业分析Statistical Modelling for Business及其相关学科的代写,服务范围广, 其中包括但不限于:

  • Statistical Inference 统计推断
  • Statistical Computing 统计计算
  • Advanced Probability Theory 高等楖率论
  • Advanced Mathematical Statistics 高等数理统计学
  • (Generalized) Linear Models 广义线性模型
  • Statistical Machine Learning 统计机器学习
  • Longitudinal Data Analysis 纵向数据分析
  • Foundations of Data Science 数据科学基础
统计代写|商业分析作业代写Statistical Modelling for Business代考|More about Surveys and Errors in Survey

统计代写|商业分析作业代写Statistical Modelling for Business代考|Types of survey questions

Survey instruments can use dichotomous (“yes or no”), multiple-choice, or open-ended questions. Each type of question has its benefits and drawbacks. Dichotomous questions are usually clearly stated, can be answered quickly, and yield data that are easily analyzed. However, the information gathered may be limited by this two-option format. If we limit voters to expressing support or disapproval for stem-cell research, we may not learn the nuanced reasoning that voters use in weighing the merits and moral issues involved. Similarly, in today’s heterogeneous world, it would be unusual to use a dichotomous question to categorize a person’s religious preferences. Asking whether respondents are Christian or non-Christian (or to use any other two categories like Jewish or non-Jewish; Muslim or nonMuslim) is certain to make some people feel their religion is being slighted. In addition, this is a crude and unenlightening way to learn about religious preferences.

Multiple-choice questions can assume several different forms. Sometimes respondents are asked to choose a response from a list (for example, possible answers to the religion question could be Jewish; Christian; Muslim; Hindu; Agnostic; or Other). Other times, respondents are asked to choose an answer from a numerical range. We could ask the question:
“In your opinion, how important are SAT scores to a college student’s success?”
Not important at all $1 \quad 2 \quad 3 \quad 4 \quad 5$ Extremely important
These numerical responses are usually summarized and reported in terms of the average response, whose size tells us something about the perceived importance. The Zagat restaurant survey (www.zagat.com) asks diners to rate restaurants’ food, décor, and service, each on a scale of 1 to 30 points, with a 30 representing an incredible level of satisfaction. Although the Zagat scale has an unusually wide range of possible ratings, the concept is the same as in the more common 5-point scale.

Open-ended questions typically provide the most honest and complete information because there are no suggested answers to divert or bias a person’s response. This kind of question is often found on instructor evaluation forms distributed at the end of a college course. College students at Georgetown University are asked the open-ended question, “What comments would you give to the instructor?’ The responses provide the instructor feedback that may be missing from the initial part of the teaching evaluation survey, which consists of numerical multiple-choice ratings of various aspects of the course. While these numerical ratings can be used to compare instructors and courses, there are no easy comparisons of the diverse responses instructors receive to the open-ended question. In fact, these responses are often seen only by the instructor and are useful, constructive tools for the teacher despite the fact they cannot be readily summarized.

Survey questionnaires must be carefully constructed so they do not inadvertently bias the results. Because survey design is such a difficult and sensitive process, it is not uncommon for a pilot survey to be taken before a lot of time, effort, and financing go into collecting a large amount of data. Pilot surveys are similar to the beta version of a new electronic product; they are tested out with a smaller group of people to work out the “kinks” before being used on a larger scale. Determination of the sample size for the final survey is an important process for many reasons. If the sample size is too large, resources may be wasted during the data collection. On the other hand, not collecting enough data for a meaningful analysis will obviously be detrimental to the study. Fortunately, there are several formulas that will help decide how large a sample should be, depending on the goal of the study and various other factors.

统计代写|商业分析作业代写Statistical Modelling for Business代考|Types of surveys

There are several different survey types, and we will explore just a few of them. The phone survey is particularly well-known (and often despised). A phone survey is inexpensive and usually conducted by callers who have very little training. Because of this and the impersonal nature of the medium, the respondent may misunderstand some of the questions. A further drawback is that some people cannot be reached and that others may refuse to answer some or all of the questions. Phone surveys are thus particularly prone to have a low response rate.
The response rate is the proportion of all people whom we attempt to contact that actually respond to a survey. A low response rate can destroy the validity of a survey’s results.
It can be difficult to collect good data from unsolicited phone calls because many of us resent the interruption. The calls often come at inopportune times, intruding on a meal or arriving just when we have climbed a ladder with a full can of paint. No wonder we may fantasize about turning the tables on the callers and calling them when it is least convenient.

Numerous complaints have been filed with the Federal Trade Commission (FTC) about the glut of marketing and survey telephone calls to private residences. The National Do Not Call Registry was created as the culmination of a comprehensive, three-year review of the Telemarketing Sales Rule (TSR) (www.ftc.gov/donotcall/). This legislation allows people to enroll their phone numbers on a website so as to prevent most marketers from calling them.
Self-administered surveys, or mail surveys, are also very inexpensive to conduct. However, these also have their drawbacks. Often, recipients will choose not to reply unless they receive some kind of financial incentive or other reward. Generally, after an initial mailing, the response rate will fall between 20 and 30 percent. Response rates can be raised with successive follow-up reminders, and after three contacts, they might reach between 65 and 75 percent. Unfortunately, the entire process can take significantly longer than a phone survey would.

Web-based surveys have become increasingly popular, but they suffer from the same problems as mail surveys. In addition, as with phone surveys, respondents may record their true reactions incorrectly because they have misunderstood some of the questions posed.
A personal interview provides more control over the survey process. People selected for interviews are more likely to respond because the questions are being asked by someone face-to-face. Questions are less likely to be misunderstood because the people conducting the interviews are typically trained employees who can clear up any confusion arising during the process. On the other hand, interviewers can potentially “lead” a respondent by body language which signals approval or disapproval of certain sorts of answers. They can also prompt certain replies by providing too much information. Mall surveys are examples of personal interviews. Interviewers approach shoppers as they pass by and ask them to answer the survey questions. Response rates around 50 percent are typical. Personal interviews are more costly than mail or phone surveys. Obviously, the objective of the study will be important in deciding upon the survey type employed.

统计代写|商业分析作业代写Statistical Modelling for Business代考|Errors of observation

As discussed in Section 1.4, the opinions of those who bother to complete a voluntary response survey may be dramatically different from those who do not. (Recall the Ann Landers question about having children.) The viewer voting on the popular television show American Idol is another illustration of selection bias, because only those who are interested in the outcome of the show will bother to phone in or text message their votes. The results of the voting are not representative of the performance ratings the country would give as a whole.
Errors of observation occur when data values are recorded incorrectly. Such errors can be caused by the data collector (the interviewer), the survey instrument, the respondent, or the data collection process. For instance, the manner in which a question is asked can influence the response. Or, the order in which questions appear on a questionnaire can influence the survey results. Or, the data collection method (telephone interview, questionnaire, personal interview, or direct observation) can influence the results. A recording error occurs when either the respondent or interviewer incorrectly marks an answer. Once data are collected from a survey, the results are often entered into a computer for statistical analysis. When transferring data from a survey form to a spreadsheet program like Excel, Minitab, or MegaStat, there is potential for entering them incorrectly. Before the survey is administered, the questions need to be very carefully worded so that there is little chance of misinterpretation. A poorly framed question might yield results that lead to unwarranted decisions. Scaled questions are particularly susceptible to this type of error. Consider the question “How would you rate this course?” Without a proper explanation, the respondent may not know whether “1” or ” 5 ” is the best.

If the survey instrument contains highly sensitive questions and respondents feel compelled to answer, they may not tell the truth. This is especially true in personal interviews. We then have what is called response bias. A surprising number of people are reluctant to be candid about what they like to read or watch on television. People tend to overreport “good” activities like reading respected newspapers and underreport their “bad” activities like delighting in the National Fnquirer’s stories of alien ahductions and celehrity meltdewns. Iniggine, then, the difficully in getting henest inswers abeut pevple’s ganbling hab its, drug use, or sexual histories. Response bias can also occur when respondents are asked slanted questions whose wording influences the answer received. For example, consider the following question:
Which of the following best describes your views on gun control?
1 The government should take away our guns, leaving us defenseless against heavily armed criminals.
2 We have the right to keep and bear arms.
This question is biased toward eliciting a response against gun control.

统计代写|商业分析作业代写Statistical Modelling for Business代考|More about Surveys and Errors in Survey


统计代写|商业分析作业代写Statistical Modelling for Business代考|Types of survey questions


“在您看来,SAT 成绩对大学生的成功有多重要?”
这些数值响应通常根据平均响应进行总结和报告,其大小告诉我们一些关于感知重要性的信息。Zagat 餐厅调查 (www.zagat.com) 要求食客对餐厅的食物、装饰和服务进行评分,每项评分从 1 到 30 分,其中 30 分代表令人难以置信的满意度。尽管 Zagat 量表具有异常广泛的可能评级范围,但其概念与更常见的 5 点量表相同。

开放式问题通常提供最诚实和最完整的信息,因为没有建议的答案来转移或偏向一个人的反应。这种问题经常出现在大学课程结束时分发的教师评估表上。乔治城大学的大学生被问到一个开放式问题,“你会给导师什么意见?” 回答提供了教师反馈,教学评估调查的初始部分可能缺少该反馈,该调查由课程各个方面的数字多项选择评分组成。虽然这些数字评分可用于比较教师和课程,但很难比较教师对开放式问题的不同回答。实际上,


统计代写|商业分析作业代写Statistical Modelling for Business代考|Types of surveys


已经向联邦贸易委员会 (FTC) 提出了大量关于私人住宅的营销和调查电话过剩的投诉。全国请勿来电登记处的创建是对电话营销销售规则 (TSR) (www.ftc.gov/donotcall/) 的三年全面审查的高潮。这项立法允许人们在网站上注册他们的电话号码,以防止大多数营销人员给他们打电话。
自我管理的调查或邮寄调查的成本也很低。然而,这些也有它们的缺点。通常,收件人会选择不回复,除非他们收到某种经济激励或其他奖励。通常,在初次邮寄后,回复率将在 20% 到 30% 之间。通过连续的后续提醒可以提高响应率,并且在三个联系之后,它们可能会达到 65% 到 75% 之间。不幸的是,整个过程可能比电话调查花费的时间要长得多。

个人访谈可以更好地控制调查过程。被选中参加面试的人更有可能做出回应,因为这些问题是由面对面的人提出的。问题不太可能被误解,因为进行采访的人通常是经过培训的员工,他们可以解决过程中出现的任何困惑。另一方面,采访者可能会通过肢体语言“引导”受访者,这表明对某些类型的回答表示赞同或不赞同。他们还可以通过提供太多信息来提示某些回复。商场调查是个人访谈的例子。采访者在购物者经过时接近他们并要求他们回答调查问题。50% 左右的响应率是典型的。个人访谈比邮件或电话调查更昂贵。明显地,

统计代写|商业分析作业代写Statistical Modelling for Business代考|Errors of observation

正如第 1.4 节所讨论的,那些费心完成自愿回答调查的人的意见可能与那些不参加的人有很大不同。(回想一下 Ann Landers 关于生孩子的问题。)热门电视节目《美国偶像》上的观众投票是选择偏见的另一个例证,因为只有那些对节目结果感兴趣的人才会费心打电话或发短信给他们的选票. 投票结果并不代表该国整体的绩效评级。
当数据值记录不正确时,就会发生观察错误。此类错误可能由数据收集者(访调员)、调查工具、受访者或数据收集过程引起。例如,提问的方式会影响回答。或者,问题出现在问卷上的顺序会影响调查结果。或者,数据收集方法(电话访谈、问卷调查、个人访谈或直接观察)会影响结果。当受访者或访问者错误地标记答案时,就会发生记录错误。从调查中收集数据后,通常会将结果输入计算机进行统计分析。将数据从调查表传输到 Excel、Minitab 或 MegaStat 等电子表格程序时,有可能输入错误。在进行调查之前,需要对问题进行非常仔细的措辞,以免产生误解。一个结构不佳的问题可能会产生导致无根据的决定的结果。比例问题特别容易受到此类错误的影响。考虑“你如何评价这门课程?”这个问题。如果没有适当的解释,被访者可能不知道“1”还是“5”是最好的。考虑“你如何评价这门课程?”这个问题。如果没有适当的解释,被访者可能不知道“1”还是“5”是最好的。考虑“你如何评价这门课程?”这个问题。如果没有适当的解释,被访者可能不知道“1”还是“5”是最好的。

如果调查工具包含高度敏感的问题,而受访者觉得有必要回答,他们可能不会说实话。在个人采访中尤其如此。然后我们就有了所谓的反应偏差。数量惊人的人不愿意坦诚他们喜欢在电视上阅读或观看的内容。人们倾向于高估“好”活动,例如阅读受人尊敬的报纸,而低估他们的“坏”活动,例如欣赏《国家调查报》关于外星人绑架和名人融化的故事。因此,Iniggine 很难得到关于 pevple 的嗜好、吸毒或性史的最新答案。当回答者被问及措辞会影响收到的答案的倾斜问题时,也会出现反应偏差。例如,考虑以下问题:
1 政府应该拿走我们的枪支,让我们对全副武装的犯罪分子束手无策。
2 我们有权持有和携带武器。

统计代写|商业分析作业代写Statistical Modelling for Business代考 请认准statistics-lab™

统计代写请认准statistics-lab™. statistics-lab™为您的留学生涯保驾护航。统计代写|python代写代考


在概率论概念中,随机过程随机变量的集合。 若一随机系统的样本点是随机函数,则称此函数为样本函数,这一随机系统全部样本函数的集合是一个随机过程。 实际应用中,样本函数的一般定义在时间域或者空间域。 随机过程的实例如股票和汇率的波动、语音信号、视频信号、体温的变化,随机运动如布朗运动、随机徘徊等等。


贝叶斯统计概念及数据分析表示使用概率陈述回答有关未知参数的研究问题以及统计范式。后验分布包括关于参数的先验分布,和基于观测数据提供关于参数的信息似然模型。根据选择的先验分布和似然模型,后验分布可以解析或近似,例如,马尔科夫链蒙特卡罗 (MCMC) 方法之一。贝叶斯统计概念及数据分析使用后验分布来形成模型参数的各种摘要,包括点估计,如后验平均值、中位数、百分位数和称为可信区间的区间估计。此外,所有关于模型参数的统计检验都可以表示为基于估计后验分布的概率报表。





随着AI的大潮到来,Machine Learning逐渐成为一个新的学习热点。同时与传统CS相比,Machine Learning在其他领域也有着广泛的应用,因此这门学科成为不仅折磨CS专业同学的“小恶魔”,也是折磨生物、化学、统计等其他学科留学生的“大魔王”。学习Machine learning的一大绊脚石在于使用语言众多,跨学科范围广,所以学习起来尤其困难。但是不管你在学习Machine Learning时遇到任何难题,StudyGate专业导师团队都能为你轻松解决。


基础数据: $N$ 个样本, $P$ 个变量数的单样本,组成的横列的数据表
变量定性: 分类和顺序;变量定量:数值
数学公式的角度分为: 因变量与自变量


随机过程,是依赖于参数的一组随机变量的全体,参数通常是时间。 随机变量是随机现象的数量表现,其时间序列是一组按照时间发生先后顺序进行排列的数据点序列。通常一组时间序列的时间间隔为一恒定值(如1秒,5分钟,12小时,7天,1年),因此时间序列可以作为离散时间数据进行分析处理。研究时间序列数据的意义在于现实中,往往需要研究某个事物其随时间发展变化的规律。这就需要通过研究该事物过去发展的历史记录,以得到其自身发展的规律。


多元回归分析渐进(Multiple Regression Analysis Asymptotics)属于计量经济学领域,主要是一种数学上的统计分析方法,可以分析复杂情况下各影响因素的数学关系,在自然科学、社会和经济学等多个领域内应用广泛。


MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中,其中问题和解决方案以熟悉的数学符号表示。典型用途包括:数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发,包括图形用户界面构建MATLAB 是一个交互式系统,其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题,尤其是那些具有矩阵和向量公式的问题,而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问,这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展,得到了许多用户的投入。在大学环境中,它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域,MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要,工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数(M 文件)的综合集合,可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。



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