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# 生物代考|生物统计学代考BIOSTATISTICS代考|BIOS654 INFERENTIAL GRAPHICAL STATISTICS

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## 生物代考|生物统计学代考BIOSTATISTICS代考|Bar and Pie Charts

In the case of qualitative or discrete data, the graphical statistics that are most often used to summarize the data in the observed sample are the bar chart and the pie chart since the
$4.2$ INFERENTIAL GRAPHICAL STATISTICS 117
important parameters of the distribution of a qualitative variable are population proportions. Thus, for a qualitative variable the sample proportions are the values that will be displayed in a bar chart or a pie chart.

In Chapter 2, the distribution of a qualitative variable was often presented in a bar chart in which the height of a bar represented the proportion or the percentage of the population having each quality the variable takes on. With an observed sample, bar charts can be used to represent the sample proportions or percentages for each of the qualities the variable takes on and can be used to make statistical inferences about the population distribution of the variable.

There are many types of bar charts including simple bar charts, stacked bar charts, and comparative side-by-side bar charts. An example of a simple bar chart for the weight classification for babies, which takes on the values normal and low, in the Birth Weight data set is shown in Figure 4.1.

Note that a bar chart represents the category percentages or proportions with bars of height equal to the percentage or proportion of sample observations falling in a particular category. The widths of the bars should be equal and chosen so that an appealing chart is produced. Bar charts may be drawn with either horizontal or vertical bars, and the bars in a bar chart may or may not be separated by a gap. An example of a bar chart with horizontal bars is given in Figure $4.2$ for the weight classification of babies in the Birth Weight data set.
In creating a bar chart it is important that

1. the proportions or percentages in each bar can be easily determined to make the bar chart easier to read and interpret.
2. the total percentage represented in the bar chart should be 100 since a distribution contains $100 \%$ of the population units.
3. the qualities associated with an ordinal variable are listed in the proper relative order! With a nominal variable the order of the categories is not important.
4. the bar chart has the axes of the bar chart clearly labeled so that it is clear whether the bars represent a percentage or a proportion.
5. the bar chart has either a caption or a title that clearly describes the nature of the bar chart.

## 生物代考|生物统计学代考BIOSTATISTICS代考|Boxplots

One of the most commonly used graphical statistics for estimating the distribution of a quantitative variable is the boxplot. A boxplot, also called a box and whisker plot, is a graphical statistic that can be used to summarize the observed sample data and can provide useful information on the shape and the tails of the population distribution. A boxplot is a simple graphical statistic that can be used to make inferences about the tails of the distribution, the typical values in the population, and the spread of the population. Boxplots are also useful in identifying extreme or unusual points in a sample, and a boxplot can also be used in comparing the distributions of two or more subpopulations.

A boxplot is based on the five-number summary associated with a sample. The fivenumber summary associated with a sample consists of the following statistics: the minimum of the sample, the maximum of the sample, the sample 25 th percentile $(Q 1)$, the sample 50 th percentile $(\tilde{x})$, and the sample 75 th percentile $(Q 3)$. The five-number summary can be used to create two types of boxplots, namely, the simple boxplot and the outlier boxplot.
A simple boxplot is a graphical statistic based on the five-number summary and an outline for constructing a simple boxplot is given below.

## 生物代考|生物统计学代考BIOSTATISTICS 代考|Boxplots

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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。