统计代写|统计计算代写Statistical calculation代考|STAT407

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couryes-lab™ 为您的留学生涯保驾护航 在代写统计计算Statistical calculation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。我们的专家在代写统计计算Statistical calculation代写方面经验极为丰富，各种代写统计计算Statistical calculation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
couryes™为您提供可以保分的包课服务

统计代写|统计计算代写Statistical calculation代考|Measures of central tendency

Measures of central tendency numerically describe the average or typical value of a data set. This is a single value that represents the whole data set. There are many averages, each having its own characteristics. For the same set of data all the averages might have different values. Three commonly used averages are:

• the arithmetic mean
• the median
• the mode.

This is the most commonly used measure of central tendency and is often referred to as the average or the mean. The sample statistic, the mean, is represented by the symbol $\bar{x}$ ( $x$-bar), and the population parameter, the mean, is represented by the Greek letter $\mu$ (‘mu’).

The mean can be seen as the centre of gravity. It is the middle of the actual numerical values of all the observations, not necessarily in the middle of the number of observations.

The arithmetic mean is the sum of all the values in a data set, divided by the number of values in the data set.
Ungrouped data
Ungrouped (or raw) data will usually be presented as a list of numbers in any order or quantity.
Where:
$\bar{x}=$ arithmetic mean
$x=$ each observation value
$n=$ number of observations

统计代写|统计计算代写Statistical calculation代考|Choose between the mean, median or mode

An average should convey an impression of a distribution in a single value. It is therefore important to use the right type of average. The different averages have different uses. The factors that play a role in choosing the right average are the following:

1. Is the nature of the data numerical or non-numerical?
• The mode, which is the value that occurs most often, is the only measure of central tendency useful for nominal scale data (qualitative data that you cannot rank in any way). You can also use the mode for all other qualitative or quantitative (numerical) data sets.
• If you can rank qualitative data sets (ordinal scale), you can use the median. The median is also valid for all quantitative data sets.
• The arithmetic mean can be calculated only for quantitative data sets.
1. What does each average tells us?
Depending on the situation and the problem under investigation, one measure may be superior to another, and in some other cases you can use all three in conjunction.
• The mode identifies the most common or ‘typical’ value, or the value that occurs more often than the others do. It may be a good choice if one value occurs much more often than others do. At the same time, the mode conveys the least amount of information about the data set as a whole. In some samples the mode may be in the middle of the distribution, but in others it may be a value at one end of the distribution. It is also possible to have more than one mode, which will eliminate the mode as an option. Outliers do not influence the mode at all and the mode stays at the peak of the distribution.
• The median indicates the centre of the distribution. The same number of observations lie above and below the median. Outliers occur at the
• beginning or end of a distribution; this means that it is unlikely that outliers will affect the median very much.
• The mean is the most frequently used average because it includes all the values in the data set. This feature makes it the most sensitive to extreme values.
• What is the shape of the distribution?
• In a symmetrical distribution, the mean, median and mode will be the same or very close together. Whichever one you choose will give you the same answer.
• If there are extreme values present on one side of the data set, the distribution is skewed. If the mean is very different from the median, the median will be a better option to use. Skewness will be discussed later in the unit.

统计计算代考

• 算术平均数
• 中位数
• 模式。

X¯=算术平均值
X=每个观测值
n=观察次数

统计代写|统计计算代写Statistical calculation代考|Choose between the mean, median or mode

1. 数据的性质是数值的还是非数值的？
• 众数是最常出现的值，是对标称尺度数据（无法以任何方式排序的定性数据）有用的集中趋势的唯一度量。您还可以将该模式用于所有其他定性或定量（数字）数据集。
• 如果您可以对定性数据集（有序量表）进行排名，则可以使用中位数。中位数也适用于所有定量数据集。
• 只能对定量数据集计算算术平均值。
1. 每个平均值告诉我们什么？
根据具体情况和所调查的问题，一种措施可能优于另一种措施，在其他一些情况下，您可以结合使用所有三种措施。
• 该模式标识最常见或“典型”值，或者比其他值更频繁出现的值。如果一个值比其他值出现的次数多得多，这可能是一个不错的选择。同时，该模式传达了关于整个数据集的最少信息量。在某些样本中，模式可能位于分布的中间，但在其他样本中，它可能是分布一端的值。也可以有不止一种模式，这将消除模式作为一个选项。离群值根本不影响模式，模式停留在分布的峰值。
• 中位数表示分布的中心。相同数量的观察值位于中值之上和之下。异常值出现在
• 分配的开始或结束；这意味着异常值不太可能对中位数产生太大影响。
• 平均值是最常用的平均值，因为它包括数据集中的所有值。此功能使其对极值最敏感。
• 分布的形状是什么？
• 在对称分布中，均值、中位数和众数将相同或非常接近。无论你选择哪一个都会给你相同的答案。
• 如果数据集的一侧存在极值，则分布是偏斜的。如果均值与中位数相差很大，则中位数将是更好的选择。偏度将在本单元后面讨论。

有限元方法代写

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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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