统计代写|AP统计作业代写代考|Levels of Measurement

(a) Taos, Acoma, Zuni, and Cochiti are the names of four Native American pueblos from the population of names of all Native American pueblos in Arizona and New Mexico.
SOLUTION: These data are at the nominal level. Notice that these data values are simply names. By looking at the name alone, we cannot determine if one name is “greater than or less than” another. Any ordering of the names would be numerically meaningless.
(b) In a high school graduating class of 319 students, Jim ranked 25 th, June ranked 19 th, Walter ranked 10th, and Julia ranked 4th, where 1 is the highest rank. SOLUTION: These data are at the ordinal level. Ordering the data clearly makes sense. Walter ranked higher than June. Jim had the lowest rank, and Julia the highest. However, numerical differences in ranks do not have meaning. The difference between June’s and Jim’s ranks is 6 , and this is the same difference that exists between Walter’s and Julia’s ranks. However, this difference doesn’t really mean anything significant. For instance, if you looked at grade point average, Walter and Julia may have had a large gap between their grade point averages, whereas June and Jim may have had closer grade point averages. In any ranking system, it is only the relative standing that matters. Computed differences between ranks are meaningless.
(c) Body temperatures (in degrees Celsius) of trout in the Yellowstone River. SOLUTION: These data are at the interval level. We can certainly order the data, and we can compute meaningful differences. However, for Celsius-scale temperatures, there is not an inherent starting point. The value $0^{\circ} \mathrm{C}$ may seem to be a starting point, but this value does not indicate the state of “no heat.” Furthermore, it is not correct to say that $20^{\circ} \mathrm{C}$ is twice as hot as $10^{\circ} \mathrm{C}$.

(d) Length of trout swimming in the Yellowstone River. SOLUTION: These data are at the ratio level. An 18-inch trout is three times as long as a 6-inch trout. Observe that we can divide 6 into 18 to determine a meaningful ratio of trout lengths.

In summary, there are four levels of measurement. The nominal level is considered the lowest, and in ascending order we have the ordinal, interval, and ratio levels. In general, ealeulations based on a partieular level of measurement may not be appropriate for a lower level.

统计代写|AP统计作业代写代考|What Does the Level of Measurement Tell Us?

The level of measurement tells us which arithmetic processes are appropriate for the data. This is important because different statistical processes require various kinds of arithmetic. In some instances all we need to do is count the number of data that meet specified criteria. In such cases nominal (and higher) data levels are all appropriate. In other cases we need to order the data, so nominal data would not be suitable. Many other statistical processes require division, so data need to be at the ratio level. Just keep the nature of the data in mind before beginning statistical computations.

统计代写|AP统计作业代写代考|Critical Thinking

“Data! Data! Data! ” he cried impatiently. “I can’t make bricks without clay.” Sherlock Holmes said these words in The Adventure of the Copper Beeches by Sir Arthur Conan Doyle.

Reliable statistical conclusions require reliable data. This section has provided some of the vocabulary used in discussing data. As you read a statistical study or conduct one, pay attention to the nature of the data and the ways they were collected.
When you select a variable to measure, be sure to specify the process and requirements for measurement. For example, if the variable is the weight of readyto-harvest pineapples, specify the unit of weight, the accuracy of measurement, and maybe even the particular scale to be used. If some weights are in ounces and others in grams, the data are fairly useless.

Another concern is whether or not your measurement instrument truly measures the variable. Just asking people if they know the geographic location of the island nation of Fiji may not provide accurate results. The answers may reflect the fact that the respondents want you to think they are knowledgeable. Asking people to locate Fiji on a map may give more reliable results.
The level of measurement is also an issue. You can put numbers into a calculator or computer and do all kinds of arithmetic. However, you need to judge whether the operations are meaningful. For ordinal data such as restaurant rankings, you can’t conclude that a 4-star restaurant is “twice as good” as a 2-star restaurant, even though the number 4 is twice 2 .Are the data from a sample, or do they comprise the entire population? Sample data can vary from one sample to another! This means that if you are studying the same statistic from two different samples of the same size, the data values may be different. In fact, the ways in which sample statistics vary among different samples of the same size will be the focus of our study from Section $6.4$ on.

AP统计代写

统计代写|AP统计作业代写代考|Identify the type of data

(a) Taos、Acoma、Zuni 和 Cochiti 是亚利桑那州和新墨西哥州所有美洲原住民普韦布洛人的名字中的四个美洲原住民普韦布洛人的名字。
解决方案：这些数据处于标称水平。请注意，这些数据值只是名称。仅通过查看名称，我们无法确定一个名称是否“大于或小于”另一个名称。名称的任何排序在数字上都是没有意义的。
(b) 在一个 319 名学生的高中毕业班中，Jim 排名第 25，June 排名第 19，Walter 排名第 10，Julia 排名第 4，其中 1 是最高排名。解决方案：这些数据处于序数级别。对数据进行排序显然是有意义的。沃尔特的排名高于六月。吉姆排名最低，朱莉娅最高。但是，等级的数值差异没有意义。June 和 Jim 的等级之间的差异是 6 ，这与 Walter 和 Julia 的等级之间存在的差异相同。但是，这种差异并不意味着任何重大意义。例如，如果您查看平均成绩，Walter 和 Julia 的平均成绩之间可能存在很大差距，而 June 和 Jim 的平均成绩可能更接近。在任何排名系统中，只有相对地位才是重要的。
(c) 黄石河中鳟鱼的体温（摄氏度）。解决方案：这些数据处于区间级别。我们当然可以对数据进行排序，并且可以计算出有意义的差异。然而，对于摄氏温度，没有固有的起点。价值0∘C似乎是一个起点，但这个值并不表示“没有热量”的状态。此外，这样说是不正确的20∘C是热的两倍10∘C.

(d) 鳟鱼在黄石河中游泳的长度。解决方案：这些数据处于比率级别。一条 18 英寸的鳟鱼是 6 英寸的鳟鱼的三倍。观察到我们可以将 6 分为 18 来确定一个有意义的鳟鱼长度比率。

总之，有四个级别的测量。名义水平被认为是最低的，按升序我们有序数、间隔和比率水平。一般而言，基于特定测量水平的评估可能不适用于较低水平。

统计代写|AP统计作业代写代考|What Does the Level of Measurement Tell Us?

测量级别告诉我们哪些算术过程适合数据。这很重要，因为不同的统计过程需要各种算术。在某些情况下，我们需要做的就是计算符合指定标准的数据数量。在这种情况下，标称（和更高）数据级别都是合适的。在其他情况下，我们需要对数据进行排序，因此名义数据不合适。许多其他统计过程需要除法，因此数据需要处于比率级别。在开始统计计算之前，请记住数据的性质。

统计代写|AP统计作业代写代考|Critical Thinking

“数据！数据！数据！”他不耐烦地叫道。“没有粘土，我不能做砖。” 夏洛克·福尔摩斯在亚瑟·柯南·道尔爵士的《铜山毛榉历险记》中说过这些话。

可靠的统计结论需要可靠的数据。本节提供了一些用于讨论数据的词汇。在阅读或进行统计研究时，请注意数据的性质和收集方式。
当您选择要测量的变量时，请务必指定测量的过程和要求。例如，如果变量是准备收获的菠萝的重量，请指定重量单位、测量精度，甚至可能要使用特定的秤。如果某些重量以盎司为单位，而另一些以克为单位，则数据是毫无用处的。

另一个问题是您的测量仪器是否真正测量了变量。仅仅询问人们是否知道斐济岛国的地理位置可能无法提供准确的结果。答案可能反映了受访者希望您认为他们知识渊博的事实。让人们在地图上定位斐济可能会得到更可靠的结果。
测量水平也是一个问题。您可以将数字输入计算器或计算机，然后进行各种算术运算。但是，您需要判断这些操作是否有意义。对于餐厅排名等序数数据，即使数字 4 是 2 的两倍，也不能得出 4 星级餐厅比 2 星级餐厅“好两倍”的结论。是来自样本的数据，还是做他们包括整个人口？样本数据可能因样本而异！这意味着，如果您从两个相同大小的不同样本中研究相同的统计数据，则数据值可能不同。事实上，相同大小的不同样本之间样本统计量的变化方式将是我们研究的重点。6.4在。

Course Overview

AP Statistics is an introductory college-level statistics course that introduces students to the major concepts and tools for collecting, analyzing, and drawing conclusions from data. Students cultivate their understanding of statistics using technology, investigations, problem solving, and writing as they explore concepts like variation and distribution; patterns and uncertainty; and data-based predictions, decisions, and conclusions.

Course Content

Based on the Understanding by Design® (Wiggins and McTighe) model, this course framework provides a clear and detailed description of the course requirements necessary for student success. The framework specifies what students must know, be able to do, and understand, with a focus on three big ideas that encompass the principles and processes in the discipline of statistics. The framework also encourages instruction that prepares students for advanced coursework in statistics or other fields using statistical reasoning and for active, informed engagement with a world of data to be interpreted appropriately and applied wisely to make informed decisions.

The AP Statistics framework is organized into nine commonly taught units of study that provide one possible sequence for the course. As always, you have the flexibility to organize the course content as you like.

Unit	Exam Weighting (Multiple-Choice Section)
Unit 1: Exploring One-Variable Data	15%–23%
Unit 2: Exploring Two-Variable Data	5%–7%
Unit 3: Collecting Data	12%–15%
Unit 4: Probability, Random Variables, and Probability Distributions	10%–20%
Unit 5: Sampling Distributions	7%–12%
Unit 6: Inference for Categorical Data: Proportions	12%–15%
Unit 7: Inference for Quantitative Data: Means	10%–18%
Unit 8: Inference for Categorical Data: Chi-Square	2%–5%
Unit 9: Inference for Quantitative Data: Slopes	2%–5%

Course Skills

The AP Statistics framework included in the course and exam description outlines distinct skills that students should practice throughout the year—skills that will help them learn to think and act like statisticians.

Skill	Description	Exam Weighting (Multiple-Choice Section)
1. Selecting Statistical Methods	Select methods for collecting and/or analyzing data for statistical inference.	15%–23%
2. Data Analysis	Describe patterns, trends, associations, and relationships in data.	15%–23%
3. Using Probability and Simulation	Explore random phenomena.	30%–40%
4. Statistical Argumentation	Develop an explanation or justify a conclusion using evidence from data, definitions, or statistical inference.	25%–35%

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

随机过程代考

在概率论概念中，随机过程是随机变量的集合。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。

贝叶斯方法代考

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。

广义线性模型代考

广义线性模型（GLM）归属统计学领域，是一种应用灵活的线性回归模型。该模型允许因变量的偏差分布有除了正态分布之外的其它分布。

statistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

机器学习代写

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。

多元统计分析代考

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

时间序列分析代写

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。

回归分析代写

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代写

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，工具箱允许您学习和应用专业技术。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。

R语言代写	问卷设计与分析代写
PYTHON代写	回归分析与线性模型代写
MATLAB代写	方差分析与试验设计代写
STATA代写	机器学习/统计学习代写
SPSS代写	计量经济学代写
EVIEWS代写	时间序列分析代写
EXCEL代写	深度学习代写
SQL代写	各种数据建模与可视化代写

统计代写|AP统计作业代写代考|Identify the type of data

统计代写|AP统计作业代写代考|What Does the Level of Measurement Tell Us?

统计代写|AP统计作业代写代考|Critical Thinking

统计代写|AP统计作业代写代考|Identify the type of data

统计代写|AP统计作业代写代考|What Does the Level of Measurement Tell Us?

统计代写|AP统计作业代写代考|Critical Thinking

Course Overview

Course Content

Course Skills

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