# 统计代写|R语言代写R language代考|NTRES6100

The basic form of the command requires the numerical vectors to be specified. If the data are inside a data frame you must use attach(), with (), or the \$$syntax to enable R to “read” them. If a single vector is specified, a one-sample test is carried out. The mu = instruction gives the location shift to test and the alternative = instruction sets the direction of the alternative hypothesis, with “two. sided” being the default. The formula syntax enables you to specify response predictor for when you have data in that format. This also allows you to specify the data so that you do not need to use attach () or with () commands or the \syntax. If you have a response variable column you have to use a more complex method to extract the sample you require. Here you used a conditional statement to select the sample and used the summary () command to determine the first quartile. This value was used as the mu = instruction along with an alternative = “greater” instruction to make a one-sided test. When you have more than two samples in a predictor variable the subset instruction enables you to select two samples to compare; the subset instruction works only with the formula syntax and you specify the samples to compare in the following way: subset = response sing c/ “sample1*, “sample2”). The U-test is a useful tool for comparing two samples and is one of the most widely used of all simple statistical tests. Both the t. test () and wilcox. test () commands can also deal with matched pair data, which you have not seen yet. This is the subject of the next section. ## 统计代写|R语言代写R language代考|Customizing Boxplots A plot without labels is useless; the plot needs labels. You can use the \mathrm{x} 1 \mathrm{ab} and \mathrm{y} 1 \mathrm{ab} instructions to label the axes. You can use the names instruction to set the labels (currently displayed as 1 and 2) for the two samples, like so:$$ \begin{aligned} &\text { > boxplot (fw\count, fw\speed, names = c(‘count’, ‘speed’)) } \ &\text { > title(xlab = ‘Variable’, ylab = ‘Value’) } \end{aligned} $$The resulting plot looks like Figure 7-3. In this case you used the title() command to add the axis labels, but you could have specified x 1 a b and y l a b within the boxplot () command. Now you have names for each of the samples as well as axis labels. Notice that the whiskers of the count sample do not extend to the top, and that you appear to have a separate point displayed. You can determine how far out the whiskers extend, but by default this is 1.5 times the interquartile range. You can alter this by using the range = instruction; if you specify range =0 as shown in the following example, the whiskers extend to the maximum and minimum values:$$ \begin{aligned} &>\text { boxplot (fwscount, fw\speed, names }=c(\text { ‘count’ ‘ ‘speed’), range }=0, \
&\text { xlab = ‘Variable’, ylab = ‘Value’, col }=\text { ‘gray } 90^{\prime} \text { ‘) }
\end{aligned}

The final graph appears like Figure 7-4. Here you not only force the whiskers to extend to the full max and min values, but you also set the box colors to a light gray. You can see which colors are available using the colors () command.

# R语言代考

## 统计代写|R语言代写R language代考|Formula Syntax and Subsetting Samples in the U-test

U 检验是比较两个样本的有用工具，是所有简单统计检验中使用最广泛的检验之一。两者都是 t。测试 () 和威尔科克斯。test() 命令还可以处理匹配对数据，这是你还没有见过的。这是下一节的主题。

## 统计代写|R语言代写R language代考|Customizing Boxplots

> 箱线图 (fw$count, fw$speed, names = c(‘count’, ‘speed’))   > title(xlab = ‘变量’, ylab = ‘值’)

> 箱线图（fwscount，fw\$speed，名字 =C( ‘计数”’速度’），范围 =0,  xlab = ‘变量’, ylab = ‘值’, col = ‘灰色的 90′ ‘)

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