h2(#description). Description

This template will return descriptive statistics of a numerical or frequency table of a categorical variable.

h3(#gender-gender). _gender_ ("Gender")

The dataset has _709_ observations with _673_ valid values (missing: _36_).

<table>
<caption>Frequency table: Gender</caption>
<col width="12%" />
<col width="5%" />
<col width="8%" />
<col width="15%" />
<col width="15%" />
<thead>
<tr class="header">
<th align="center">gender</th>
<th align="center">N</th>
<th align="center">%</th>
<th align="center">Cumul. N</th>
<th align="center">Cumul. %</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="center">male</td>
<td align="center">410</td>
<td align="center">60.92</td>
<td align="center">410</td>
<td align="center">60.92</td>
</tr>
<tr class="even">
<td align="center">female</td>
<td align="center">263</td>
<td align="center">39.08</td>
<td align="center">673</td>
<td align="center">100</td>
</tr>
<tr class="odd">
<td align="center">Total</td>
<td align="center">673</td>
<td align="center">100</td>
<td align="center">673</td>
<td align="center">100</td>
</tr>
</tbody>
</table>

The most frequent value is _male_.

h4(#charts). Charts

"!plots/Descriptives-1.png(Barplot: Gender)!":plots/Descriptives-1-hires.png

h2(#description-1). Description

This template will return descriptive statistics of a numerical or frequency table of a categorical variable.

h3(#age-age). _age_ (&quot;Age&quot;)

The dataset has _709_ observations with _677_ valid values (missing: _32_).

h4(#base-statistics). Base statistics

<table>
<caption>Descriptives: Age</caption>
<col width="15%" />
<col width="9%" />
<col width="8%" />
<col width="8%" />
<thead>
<tr class="header">
<th align="center">Variable</th>
<th align="center">mean</th>
<th align="center">sd</th>
<th align="center">var</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="center">Age</td>
<td align="center">24.57</td>
<td align="center">6.849</td>
<td align="center">46.91</td>
</tr>
</tbody>
</table>

The "standard deviation":http://en.wikipedia.org/wiki/Standard_deviation equals to _6.849_ (variance: _46.91_), which shows the unstandardized degree of "homogenity":http://en.wikipedia.org/wiki/Homogeneity_(statistics): how much variation exists from the average. The "expected value":http://en.wikipedia.org/wiki/Mean is around _24.57_, somewhere between _24.06_ and _25.09_ with the standard error of _0.2632_.

The highest value found in the dataset is _58_, which is exactly _3.625_ times higher than the minimum (_16_). The difference between the two is described by the "range":http://en.wikipedia.org/wiki/Range_(statistics): _42_.

h4(#chart). Chart

A "histogram":http://en.wikipedia.org/wiki/Histogram visually shows the "distribution":http://en.wikipedia.org/wiki/Probability_distribution of the dataset based on artificially allocated "frequencies":http://en.wikipedia.org/wiki/Statistical_frequency. Each bar represents a theoretical interval of the data, where the height shows the count or density.

"!plots/Descriptives-2.png(Histogram: Age)!":plots/Descriptives-2-hires.png

If we _suppose_ that _Age_ is not near to the "normal distribution":http://en.wikipedia.org/wiki/Normal_distribution (see for example "skewness":http://en.wikipedia.org/wiki/Skewness: _1.925_, "kurtosis":http://en.wikipedia.org/wiki/Kurtosis: _4.463_), checking the median (_23_) might be a better option instead of the mean. The "interquartile range":http://en.wikipedia.org/wiki/Interquartile_range (_6_) measures the statistics dispersion of the variable (similar to standard deviation) based on median.

h2(#description-2). Description

This template will return descriptive statistics of a numerical or frequency table of a categorical variable.

h3(#hp). _hp_

The dataset has _32_ observations with _32_ valid values (missing: _0_).

h4(#base-statistics-1). Base statistics

<table>
<caption>Descriptives: hp</caption>
<col width="15%" />
<col width="9%" />
<col width="8%" />
<col width="8%" />
<thead>
<tr class="header">
<th align="center">Variable</th>
<th align="center">mean</th>
<th align="center">sd</th>
<th align="center">var</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td align="center">hp</td>
<td align="center">146.7</td>
<td align="center">68.56</td>
<td align="center">4701</td>
</tr>
</tbody>
</table>

The "standard deviation":http://en.wikipedia.org/wiki/Standard_deviation equals to _68.56_ (variance: _4701_), which shows the unstandardized degree of "homogenity":http://en.wikipedia.org/wiki/Homogeneity_(statistics): how much variation exists from the average. The "expected value":http://en.wikipedia.org/wiki/Mean is around _146.7_, somewhere between _122.9_ and _170.4_ with the standard error of _12.12_.

The highest value found in the dataset is _335_, which is exactly _6.442_ times higher than the minimum (_52_). The difference between the two is described by the "range":http://en.wikipedia.org/wiki/Range_(statistics): _283_.

h4(#chart-1). Chart

A "histogram":http://en.wikipedia.org/wiki/Histogram visually shows the "distribution":http://en.wikipedia.org/wiki/Probability_distribution of the dataset based on artificially allocated "frequencies":http://en.wikipedia.org/wiki/Statistical_frequency. Each bar represents a theoretical interval of the data, where the height shows the count or density.

"!plots/Descriptives-3.png(Histogram: hp)!":plots/Descriptives-3-hires.png

If we _suppose_ that _hp_ is not near to the "normal distribution":http://en.wikipedia.org/wiki/Normal_distribution (see for example "skewness":http://en.wikipedia.org/wiki/Skewness: _0.726_, "kurtosis":http://en.wikipedia.org/wiki/Kurtosis: _-0.1356_), checking the median (_123_) might be a better option instead of the mean. The "interquartile range":http://en.wikipedia.org/wiki/Interquartile_range (_83.5_) measures the statistics dispersion of the variable (similar to standard deviation) based on median.

<hr />

This report was generated with "R":http://www.r-project.org/ (3.0.1) and "rapport":https://rapporter.github.io/rapport/ (0.51) in _1.105_ sec on x86&#95;64-unknown-linux-gnu platform.

!images/logo.png!