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

The dataset has *709* observations with *673* valid values (missing: *36*).

gender | N | % | Cumul. N | Cumul. % |
---|---|---|---|---|

male | 410 | 60.92 | 410 | 60.92 |

female | 263 | 39.08 | 673 | 100 |

Total | 673 | 100 | 673 | 100 |

The most frequent value is *male*.

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

The dataset has *709* observations with *677* valid values (missing: *32*).

Variable | mean | sd | var |
---|---|---|---|

Age | 24.57 | 6.849 | 46.91 |

The standard deviation equals to *6.849* (variance: *46.91*), which shows the unstandardized degree of homogenity: how much variation exists from the average. The expected value 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: *42*.

A histogram visually shows the distribution of the dataset based on artificially allocated frequencies. Each bar represents a theoretical interval of the data, where the height shows the count or density.

If we *suppose* that *Age* is not near to the normal distribution (see for example skewness: *1.925*, kurtosis: *4.463*), checking the median (*23*) might be a better option instead of the mean. The interquartile range (*6*) measures the statistics dispersion of the variable (similar to standard deviation) based on median.

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

The dataset has *32* observations with *32* valid values (missing: *0*).

Variable | mean | sd | var |
---|---|---|---|

hp | 146.7 | 68.56 | 4701 |

The standard deviation equals to *68.56* (variance: *4701*), which shows the unstandardized degree of homogenity: how much variation exists from the average. The expected value 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: *283*.

A histogram visually shows the distribution of the dataset based on artificially allocated frequencies. Each bar represents a theoretical interval of the data, where the height shows the count or density.

If we *suppose* that *hp* is not near to the normal distribution (see for example skewness: *0.726*, kurtosis: *-0.1356*), checking the median (*123*) might be a better option instead of the mean. The interquartile range (*83.5*) measures the statistics dispersion of the variable (similar to standard deviation) based on median.

This report was generated with R (3.0.1) and rapport (0.51) in *1.105* sec on x86_64-unknown-linux-gnu platform.