这是一篇来自美国的关于通过学习到的数据分析方法描述一个研究场景并指定一个研究问题的R语言数据分析代写,作业详情可咨询客服

 

1.作业说明

从可用的公共数据集中选择一个小的数据集

根据我们在课堂上学习到的数据分析方法,描述一个研究场景并指定一个研究问题,例如,一种和两种样本均值,t检验,相关性检验,简单多元线性回归,ANOVA和ANCOVA等方法以及比例和逻辑回归的两样本检验。

如果您的数据集很大,请清理数据并将其减少到不超过500个观察值。

2.研究方案说明(不超过200个单词)

用不超过200个字描述您的研究方案。这是用例的一般描述。与班级示例类似,我们首先描述总体情况,然后在此基础上指定一个特定的研究问题。

3.描述数据集(不超过200个字)

简要描述数据集。如果在分析中使用列,请描述数据集的每一列。使用前清理数据,例如,您可以删除异常值。删除未使用的列。如果可能,提供指向主数据集源的链接。

3.研究问题(不超过100个字)

用一两个句子简要描述主要研究问题。这类似于我们的课程示例的最后一句话。

4.您的解决方案R代码

在此处复制您的R代码。从读取数据文件中的数据开始。保持以下数据读取行。

这类似于我们的R代码示例之一。

5.执行您的R代码,然后在此框中复制和粘贴结果。

运行您的代码并将代码输出复制到此处。

1. Assignment Description

Select a small data set from the available public data sets 

Describe a research scenario and specify a research question based on data analytic methods that we learned in our class, for example methods like, one and two sample means, t-test, correlation tests, simple and multiple linear regression, ANOVA and ANCOVA, one and two-Sample Tests for Proportions and logistic regression.

Clean up your data and reduce it to no more than 500 observations if your data set is large.

2. Research Scenario Description (no more than 200 words)

Describe your research scenario in no more than 200 words.  This is a general description of the use case. Similar to our class examples, we first describe the overall scenario and then we specify a specific research question based on it.

3. Describe the data set (no more than 200 words)

Describe briefly the data set. Describe each columns of the data set if you use the column in your analysis. Clean up your data before usage, for example you can remove the outliers. Remove unused columns. If possible provide a Link to the main data set source.

3. Research Question (no more than 100 words)

Describe briefly in one or two sentences the main research question.  This is similar to the last sentence of our class examples.

4. Your solution R code

Copy your R code here. Start from read the data from a data file. Keep the following data read line.

This is similar to one of our R code examples.

5. Execute your R code, Copy and Paste results here in this Box.

Run your code and copy the output of your code to here.