### 统计代写|AP统计辅导AP统计答疑|Samples, Experiments, and Simulations

AP统计学与大学的统计学课程在核心内容上是一致的，只是涉及的深度稍浅，AP统计学主要包含以下四部分内容。 第一部分 如何获取数据，获取数据的方式有哪些呢？ 获取数据的方式主要包括普查、抽样调查、观测研究和实验设计等。

statistics-lab™ 为您的留学生涯保驾护航 在代写AP统计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AP统计代写方面经验极为丰富，各种代写AP统计相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (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|AP统计辅导AP统计答疑|Sampling

It is imperative that we follow proper data collection methods when gathering data. Statistical inference is the process by which we draw conclusions about an entire population based on sample data. Whether we are designing an experiment or sampling part of a population, it’s critical that we understand how to correctly gather the data we use. Improper data collection leads to incorrect assumptions and predictions about the population of interest. If you learn nothing else about statistics, I hope you learn to be skeptical about how data is collected and to interpret the data correctly. Properly collected data can be extremely useful in many aspects of everyday life. Inference based on data that was poorly collected or obtained can be misleading and lead us to incorrect conclusions about the population.

• You will encounter certain types of sampling in AP Statistics. As always, it’s important that you fully understand all the concepts discussed in this chapter. We begin with some basic definitions.
• A population is all the individuals in a particular group of interest. We might be interested in how the student body of our high school views a new policy about cell phone usage in school. The population of interest is all students in the school. We might take a poll of some students at lunch or during English class on a particular day. The students we poll are considered a sample of the entire population. If we sample the entire student body, we are actually conducting a census. A census consists of all individuals in the entire population. The U.S. Census attempts to count every resident in the United States and is required by the Constitution every ten years. The data collected by the U.S. Census

will help determine the number of seats each state has in the House of Representatives. There has even been some political debate on whether or not the U.S. should spend money trying to count everyone when information could be gained by using appropriate sampling techniques.

• A sampling frame is a list of individuals from the entire population from which the sample is drawn.

## 统计代写|AP统计辅导AP统计答疑|Designing Experiments

• Now that we’ve discussed some different types of sampling, it’s time to turn our attention to experimental design. It’s important to understand both observational studies and experiments and the difference between them. In an observational study, we are observing individuals. We are studying some variable about the individuals but not imposing any treatment on them. We are simply studying what is already happening. In an experiment, we are actually imposing a treatment on the individuals and studying some variable associated with that treatment. The treatment is what is applied to the subjects or experimental units. We use the term “subjects” if the experimental units are humans. The treatments may have one or more factors, and each factor may have one or more levels.
• Example 1: Consider an experiment where we want to test the effects of a new laundry detergent. We might consider two factors: water temperature and laundry detergent. The first factor, temperature, might have three levels: cold, warm, and hot water. The second factor, detergent, might have two levels: new detergent and old detergent. We can combine these to form six treatments as listed in Figure 4.1.
• It’s important to note that we cannot prove or even imply a cause-andeffect relationship with an observational study. We can, however, prove a cause-and-effect relationship with an experiment. In an experiment, we observe the relationship between the explanatory and response variables and try to determine if a cause-and-effect relationship really does exist.
• The first type of experiment that we will discuss is a completely randomized experiment. In a completely randomized experiment, subjects or experimental units are randomly assigned to a treatment group. Completely randomized experiments can be used to compare any number of treatments. Groups of equal size should be used, if possible.

## 统计代写|AP统计辅导AP统计答疑|Simulation

• Simulation can be used in statistics to model random or chance behavior. In much the same way an airplane simulator models how an actual aircraft flies, simulation can be used to help us predict the probability of some real-life occurrences. For our purposes in AP Statistics, we’ll try to keep it simple. If you are asked to set up a simulation in class or even on an exam, keep it simple. Use things like the table of random digits, a coin, a die, or a deck of cards to model the behavior of the random phenomenon.

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## 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。