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# 数据科学代写|数据可视化代写Data Visualization代考|BAN271 Relative Frequency and Percent Frequency

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## 数据科学代写|数据可视化代写Data Visualization代考|Relative Frequency and Percent Frequency

A frequency distribution, such as the one in Figure $5.4$, shows the number (count) of items in each of several nonoverlapping bins. However, we are often interested in the proportion, or percentage, of items in each bin. The relative frequency of a bin equals the fraction or proportion of items belonging to a class. For a data set with $n$ observations, the relative frequency of each bin can be determined as follows:
$$\text { Relative frequency of a bin }=\frac{\text { Frequency of the bin }}{n}$$
Often a relative frequency is expressed as a percentage. The percent frequency of a bin is the relative frequency multiplied by 100 . To obtain a percent frequency distribution for the data in the Pop file, we continue from the PivotTable in Figure $5.4$ with the following steps:
Step 1. Select any cell in the Count of Soft Drink Purchase column of the PivotTable (any cell in range B3:B8)
Step 2. When the PivotTable Fields task pane appears:
In the Values area, select the triangle to the right of Count of Soft Drink
Purchase Count of Soft Drink Purchase
Select Value Field Settings… from the list of options.
Step 3. When the Value Field Settings dialog box appears:
Click the Show Values As tab and in the box below Show values as select $\%$ of Grand Total

Figure $5.6$ shows the result of the preceding steps. The percent frequency for Coca-Cola is $190 / 500=0.38=38 \%$, the percent frequency for Pepsi is $130 / 500=0.26=16 \%$, and so on. We can also note that $38 \%+26 \%+16 \%=80 \%$ of the purchases were the top three soft drinks.
A percent frequency distribution can be used to provide estimates of the relative likelihoods of different values for a random variable. So, by constructing a percent frequency distribution from observations of a random variable, we can estimate the probability distribution that characterizes its variability. For example, suppose that a concession stand has determined it will procure a total of 12,000 ounces of soft drinks for an upcoming concert, but it is uncertain how to divide this total over the individual soft drink types. However, if the data in the Pop file are representative of the concession stand’s customer population, the manager can use this information to determine appropriate volumes of each type of soft drink. For example, the data suggest that the manager should procure $12,000 \times 0.38=4,560$ ounces of Coca-Cola.

## 数据科学代写|数据可视化代写Data Visualization代考|Visualizing Distributions of Quantitative Data

As with categorical data, we can create frequency distributions for quantitative data, but we must be more careful in defining the nonoverlapping bins to be used in the frequency distribution. Recall that for categorical data, a frequency distribution’s bins are based on the different categories. For quantitative data, each bin in the frequency distribution is based on the range of values that the bin contains.

To create a frequency distribution for quantitative data, three features need to be defined:

1. The number of nonoverlapping bins
2. The width (numerical range) of each bin
3. The range spanned by the set of bins
Excel possesses functionality that automatically defines each of these features. To demonstrate, consider a data set that contains the age at death for 700 individuals. Figure $5.8$ displays a portion of this data, contained in the file Death. The following steps construct the histogram in Figure $5.9$ illustrating the distribution of the ages at death.
Step 1. Select cells A1:A701
Step 2. Click the Insert tab on the Ribbon
Step 3. Click the Insert Statistic Chart button $\mathbb{l l}^{\vee} \vee$ in the Charts group
When the list of statistic charts appears, select Histogram 1 Hh

## 数据科学代写数据可视化代写Data Visualization代考|Relative Frequency and Percent Frequency

Relative frequency of a bin $=\frac{\text { Frequency of the bin }}{n}$

$130 / 500=0.26=16 \%$ ，等等。我们还可以住意到 $38 \%+26 \%+16 \%=80 \%$ 购买量中排名前三的软饩料。

## 数据科学代写|数据可视化代写Data Visualization代考|Visualizing Distributions of Quantitative Data

1. 非重腚 bin 的数量
2. 每个 bin 的宽度（数值范围）
3. 由一组 bin 跨越的范围
Excel 具有自动定义这些特征中的每一个的功能。为了演示，考虑一个包含 700 个人的死亡年龄的数据集。数字 $5.8$ 显示该 数据的一部分，包含在文件 Death 中。下面的步骙构建了图中的直方图 $5.9$ 说明死亡年齡的分布。
步骤 1. 选择单元格 Al:A701
步骤 2. 单击功能区上的揷入选项卡
步骤 3. 单击揷入统计图表㧍铒 $\vee \vee \vee$ 在图表组
中出现统计图表列表时，选译直方图 $1 \mathrm{Hh}$

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