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生物代考|生物统计学代考BIOSTATISTICS代考|MPH701 Histograms

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生物代考|生物统计学代考BIOSTATISTICS代考|Histograms

A second graphical statistic that provides statistical information about the distribution of a quantitative variable based on a sample is the histogram. A histogram is a vertical bar chart drawn over a set of class intervals that cover the range of the observed data. Furthermore, because the histogram is based on the entire sample and not just the five-number summary associated with the sample, a histogram generally will provide more information about a distribution than a boxplot will. An example of a histogram is given in Figure 4.13.

Histograms are particularly useful for continuous variables and can be used to make statistical inferences about the shape of a distribution, the tails of the distribution, the modes of the distribution, the typical values in the distribution, the spread of the distribution, and the percentage of the distribution falling between a specified range of values. Histograms can also be used for determining a reasonable probability distribution for modeling the distribution of the target population. Several examples of histograms and their key features are given in Figure 4.14.

生物代考|生物统计学代考BIOSTATISTICS代考|Normal Probability Plots

A boxplot and a histogram often suggest a plausible probability model that could be used for the underlying distribution. Moreover, in many cases the boxplot and histogram suggest that the distribution is mound shaped, and hence, the normal probability model should be considered a possible probability model for the distribution. A normal probability plot is a graphical statistic that can be used to assess the fit of a normal distribution to the observed data. A normal probability plot is also often referred to as a normal plot. An example of a normal probability plot is given in Figure $4.21$ for the birth weights of babies in the Birth Weight data set for mothers who smoked during pregnancy.

There are many different forms of a normal probability plot, and since each statistical package handles a normal probability plot differently, the details of creating a normal plot will not be discussed here. Regardless of how a normal probability plot is created, each normal plot can be used visually to assess whether or not it is plausible that the sampled data for a continuous variable came from a normal distribution. Normal plots are basically plots of the sample percentiles versus the expected percentiles of the normal distribution that best fits the observed sample. When the points in a normal plot fall nearly on a straight line, it is reasonable to assume that the sample data came from a normal distribution; when the points in a normal plot deviate from a straight line, the normal probability plot is suggesting that data came from a distribution that is not normally distributed.

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。