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

avatest.org生物统计学Biostatistics代写，免费提交作业要求， 满意后付款，成绩80\%以下全额退款，安全省心无顾虑。专业硕 博写手团队，所有订单可靠准时，保证 100% 原创。avatest.org， 最高质量的生物统计学Biostatistics作业代写，服务覆盖北美、欧洲、澳洲等 国家。 在代写价格方面，考虑到同学们的经济条件，在保障代写质量的前提下，我们为客户提供最合理的价格。 由于统计Statistics作业种类很多，同时其中的大部分作业在字数上都没有具体要求，因此生物统计学Biostatistics作业代写的价格不固定。通常在经济学专家查看完作业要求之后会给出报价。作业难度和截止日期对价格也有很大的影响。

my-assignmentexpert™ 为您的留学生涯保驾护航 在网课代写方面已经树立了自己的口碑, 保证靠谱, 高质且原创的网课代写服务。我们的专家在生物统计学Biostatistics代写方面经验极为丰富，各种生物统计学Biostatistics相关的作业也就用不着 说。

## 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。

Posted on Categories:Biostatistics, 生物代写, 生物统计学

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

avatest.org生物统计学Biostatistics代写，免费提交作业要求， 满意后付款，成绩80\%以下全额退款，安全省心无顾虑。专业硕 博写手团队，所有订单可靠准时，保证 100% 原创。avatest.org， 最高质量的生物统计学Biostatistics作业代写，服务覆盖北美、欧洲、澳洲等 国家。 在代写价格方面，考虑到同学们的经济条件，在保障代写质量的前提下，我们为客户提供最合理的价格。 由于统计Statistics作业种类很多，同时其中的大部分作业在字数上都没有具体要求，因此生物统计学Biostatistics作业代写的价格不固定。通常在经济学专家查看完作业要求之后会给出报价。作业难度和截止日期对价格也有很大的影响。

my-assignmentexpert™ 为您的留学生涯保驾护航 在网课代写方面已经树立了自己的口碑, 保证靠谱, 高质且原创的网课代写服务。我们的专家在生物统计学Biostatistics代写方面经验极为丰富，各种生物统计学Biostatistics相关的作业也就用不着 说。

## 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

$\mathrm{~ 简 单 箱 伐 图 是 基 于 五 数 汇 总 的 图 形 统 计 ， 下 面 哈 出 了 构 建 简 单 箱 帴 图 的 大 垚}$

## 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。

Posted on Categories:Biostatistics, 生物代写, 生物统计学

## 生物代考|生物统计学代考BIOSTATISTICS代考|BIOL220 The Sample Size for Simple and Systematic Random Samples

avatest.org生物统计学Biostatistics代写，免费提交作业要求， 满意后付款，成绩80\%以下全额退款，安全省心无顾虑。专业硕 博写手团队，所有订单可靠准时，保证 100% 原创。avatest.org， 最高质量的生物统计学Biostatistics作业代写，服务覆盖北美、欧洲、澳洲等 国家。 在代写价格方面，考虑到同学们的经济条件，在保障代写质量的前提下，我们为客户提供最合理的价格。 由于统计Statistics作业种类很多，同时其中的大部分作业在字数上都没有具体要求，因此生物统计学Biostatistics作业代写的价格不固定。通常在经济学专家查看完作业要求之后会给出报价。作业难度和截止日期对价格也有很大的影响。

my-assignmentexpert™ 为您的留学生涯保驾护航 在网课代写方面已经树立了自己的口碑, 保证靠谱, 高质且原创的网课代写服务。我们的专家在生物统计学Biostatistics代写方面经验极为丰富，各种生物统计学Biostatistics相关的作业也就用不着 说。

## 生物代考|生物统计学代考BIOSTATISTICS代考|The Sample Size for Simple and Systematic Random Samples

In a simple random sample or a systematic random sample, the sample size required to produce a prespecified bound on the error of estimation for estimating the mean is based on the number of units in the population $(N)$, and the approximate variance of the population $\sigma^{2}$. Moreover, given the values of $N$ and $\sigma^{2}$, the sample size required for estimating a mean $\mu$ with bound on the error of estimation $B$ with a simple or systematic random sample is
$$n=\frac{N \sigma^{2}}{(N-1) D+\sigma^{2}}$$
where $D=\frac{B^{2}}{4}$. Note that this formula will not generally return a whole number for the sample size $n$; when the formula does not return a whole number for the sample size, the sample size should be taken to be the next largest whole number.
Example $3.11$
Suppose a simple random sample is going to be taken from a population of $N=5000$ units with a variance of $\sigma^{2}=50$. If the bound on the error of estimation of the mean is supposed to be $B=1.5$, then the sample size required for the simple random sample selected from this population is
$$n=\frac{5000(50)}{4999\left(\frac{1.52}{4}\right)+50}=87.35$$
Since $87.35$ units cannot be sampled, the sample size that should be used is $n=88$. Also, $n=$ 88 would be the sample size required for a systematic random sample from this population when the desired bound on the error of estimation for estimating the mean is $B=1.5$. In this case, the systematic random sample would be a 1 in 56 systematic random sample since $\frac{5000}{88} \approx 56$.

## 生物代考|生物统计学代考BIOSTATISTICS代考|The Sample Size for a Stratified Random Sample

Recall that a stratified random sample is simply a collection of simple random samples selected from the subpopulations in the target population. In a stratified random sample, there are two sample size considerations, namely, the overall sample size $n$ and the allocation of $n$ units over the strata. When there are $k$ strata, the strata sample sizes will be denoted by $n_{1}, n_{2}, n_{3}, \ldots, n_{k}$, where the number to be sampled in strata 1 is $n_{1}$, the number to be sampled in strata 2 is $n_{2}$, and so on.

There are several different ways of determining the overall sample size and its allocation in a stratified random sample. In particular, proportional allocation and optimal allocation are two commonly used allocation plans. Throughout the discussion of these two allocation plans, it will be assumed that the target population has $k$ strata, $N$ units, and $N_{j}$ is the number of units in the $j$ th stratum.

The sample size used in a stratified random sample and the most efficient allocation of the sample will depend on several factors including the variability within each of the strata, the proportion of the target population in each of the strata, and the costs associated with sampling the units from the strata. Let $\sigma_{i}$ be the standard deviation of the $i$ th stratum, $W_{i}=N_{i} / N$ the proportion of the target population in the $i$ th stratum, $C_{0}$ the initial cost of sampling, $C_{i}$ the cost of obtaining an observation from the $i$ th stratum, and $C$ is the total cost of sampling. Then, the cost of sampling with a stratified random sample is
$$C=C_{0}+C_{1} n_{1}+C_{2} n_{2}+\cdots+C_{k} n_{k}$$
The process of determining the sample size for a stratified random sample requires that the allocation of the sample be determined first. The allocation of the sample size $n$ over the $k$ strata is based on the sampling proportions that are denoted by $w_{1}, w_{2}, \ldots w_{k}$. Once the sampling proportions and the overall sample size $n$ have been determined, the $i$ th stratum sample size is $n_{i}=n \times w_{i}$.

The simplest allocation plan for a stratified random sample is proportional allocation that takes the sampling proportions to be proportional to the strata sizes. Thus, in proportional allocation, the sampling proportion for the $i$ th stratum is equal to the proportion of the population in the $i$ th stratum. That is, the sampling proportion for the $i$ th stratum is
$$w_{i}=\frac{N_{i}}{N}$$

## 生物代考|生物统计学代考BIOSTATISTICS 代考|The Sample Size for Simple and Systematic Random Samples

$$n=\frac{N \sigma^{2}}{(N-1) D+\sigma^{2}}$$

$$n=\frac{5000(50)}{4999\left(\frac{1.52}{4}\right)+50}=87.35$$

## 生物代考|生物统计学代考BIOSTATISTICS 代考|The Sample Size for a Stratified Random Sample

$$C=C_{0}+C_{1} n_{1}+C_{2} n_{2}+\cdots+C_{k} n_{k}$$

$$w_{i}=\frac{N_{i}}{N}$$

## 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。