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。

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• 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统计代写AP统计代考|Position of a Term in a Distribution

Up until now, we have concentrated on the nature of a distribution as a whole. We have been concerned with the shape, center, and spread of the entire distribution. Now we look briefly at individual terms in the distribution.
Five-Number Summary
There are positions in a dataset that give us valuable information about the dataset. The five-number summary of a dataset is composed of the minimum value, the lower quartile, the median, the upper quartile, and the maximum value.

On the TI-83/84, these are reported on the second screen of data when you do 1-Var Stats as: $\min \mathrm{X}, \mathrm{Q} 1$, Med, Q3, and $\max \mathrm{X}$.
example: The following data are standard of living indices for 20 cities: 2.8, 3.9, $4.6,5.3,10.2,9.8,7.7,13,2.1,0.3,9.8,5.3,9.8,2.7,3.9,7.7,7.6,10.1,8.4$, 8.3. Find the 5-number summary for the data.
solution: Put the 20 values into a list on your calculator and do 1 -var Stats. We find: $\min X=0.3, Q 1=3.9, \mathrm{Med}=7.65, \mathrm{Q} 3=9.8$, and $\max X=13$.
Boxplots (Outliers Revisited)
In the first part of this chapter, we discussed three types of graphs: dotplot, stemplot, and histogram. Using the five-number summary, we can add a fourth type of one-variable graph to this group: the boxplot. A boxplot is simply a graphical version of the five-number summary. A box is drawn that contains the middle $50 \%$ of the data (from $\mathrm{Q} 1$ to $\mathrm{Q} 3$ ) and “whiskers” extend from the lines at the ends of the box (the lower and upper quartiles) to the minimum and maximum values of the data if there are no outliers. If there are outliers, the “whiskers” extend to the last value before the outlier that is not an outlier.

## 统计代写|AP统计代写AP统计代考|Normal Distribution

We have been discussing characteristics of distributions (shape, center, spread) and of the individual terms (percentiles, $z$-scores) that make up those distributions. Certain distributions have particular interest for us in statistics, in particular those that are known to be symmetric and mound shaped. The following histogram represents the heights of 100 males whose average height is $70^{\prime \prime}$ and whose standard deviation is $3^{\prime \prime}$.

This is clearly approximately symmetric and mound shaped. We are going to model this with a curve that idealizes what we see in this sample of 100 . That is, we will model this with a continuous curve that “describes” the shape of the distribution for very large samples. That curve is the graph of the normal distribution. A normal curve, when superimposed on the above histogram, looks like this:

The function that yields the normal curve is defined completely in terms of its mean and standard deviation. Although you are not required to know it, you might be interested to know that the function that defines the normal curve is:
$$f(x)=\frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{2}{2}\left(\frac{x-x}{\sigma}\right)^{2}} .$$
One consequence of this definition is that the total area under the curve, and above the $\mathrm{x}$-axis, is 1 (for you calculus students, this is because $\int_{-x}^{x} \frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^{2}} d x=1$ ).

This fact will be of great use to us later when we consider areas under the normal curve as probabilities.

# AP统计代写

## 统计代写|AP统计代写AP统计代考|Normal Distribution

$$f(x)=\frac{1}{\sigma \sqrt{2 \pi}} e^{-\frac{2}{2}\left(\frac{x x}{\sigma}\right)^{2}} .$$

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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。

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