English	Русский
statistic/stəˈtɪstɪk/	статистикой
descriptive statistics/dɪˈskrɪptɪv stəˈtɪstɪks/	описательная статистика
inferential statistics/ɪnfəˈrenʃl stəˈtɪstɪks/	инференциальная статистика
variable/ˈveərɪəbl/	переменной
Categorical/ˌkætɪˈɡɒrɪkl/	Категориальная
Quantitative/ˈkwɒntɪteɪtɪv/	Количественная
frequency table/ˈfriːkwənsi ˈteɪbl/	таблица частот
relative frequency/ˈrelətɪv ˈfriːkwənsi/	относительная частота
proportion/prəˈpɔːʃn/	доли
Bar charts/bɑː tʃɑːts/	столбчатые диаграммы
dotplot/ˈdɒtplɒt/	точечный график
stem-and-leaf plot/stem ænd liːf plɒt/	график «стебель-листья»

English	Русский
Statistics/stəˈtɪstɪks/	Статистика
data/ˈdeɪtə/	данные
variation/ˌveərɪˈeɪʃn/	вариация
parameter/pəˈræmɪtə/	параметром
histogram/ˈhɪstəɡræm/	гистограмма

English	Русский
distribution/ˌdɪstrɪˈbjuːʃn/	распределение
Shape/ʃeɪp/	Фигура
skewed/skjuːd/	асимметричное
unimodal/ˌʌnɪˈmɒdl/	унимодальный
bimodal/baɪˈmɒdl/	бимодальный
uniform/ˈjuːnɪfɔːm/	однородное
Outliers/ˈaʊtlaɪəz/	выбросы (outliers)
mean/miːn/	среднее значение
median/ˈmiːdiːən/	медианой
interquartile range/ˌɪntəˈkwɔːtaɪl reɪndʒ/	межквартильный размах

Enduring Understanding	Learning Objective	Essential Knowledge
UNC-1 Graphical representations and statistics allow us to identify and represent key features of data.	UNC-1.I Calculate measures of center and position for quantitative data. [Skill 2.C]	UNC-1.I.1 A statistic is a numerical summary of sample data. UNC-1.I.2 The mean is the sum of all the data values divided by the number of values. For a sample, the mean is denoted by $x$-bar: $\bar{x} = \dfrac{1}{n}\sum_{i=1}^{n} x_i$, where $x_i$ represents the $i^{\text{th}}$ data point in the sample and $n$ represents the number of data values in the sample. UNC-1.I.3 The median of a data set is the middle value when data are ordered. When the number of data points is even, the median can take on any value between the two middle values. In AP Statistics, the most commonly used value for the median of a data set with an even number of values is the average of the two middle values. UNC-1.I.4 The first quartile, Q1, is the median of the half of the ordered data set from the minimum to the position of the median. The third quartile, Q3, is the median of the half of the ordered data set from the position of the median to the maximum. Q1 and Q3 form the boundaries for the middle 50% of values in an ordered data set. UNC-1.I.5 The $p^{\text{th}}$ percentile is interpreted as the value that has $p\%$ of the data less than or equal to it.
	UNC-1.J Calculate measures of variability for quantitative data. [Skill 2.C]	UNC-1.J.1 Three commonly used measures of variability (or spread) in a distribution are the range, interquartile range, and standard deviation. UNC-1.J.2 The range is defined as the difference between the maximum data value and the minimum data value. The interquartile range (IQR) is defined as the difference between the third and first quartiles: $Q3 - Q1$. Both the range and the interquartile range are possible ways of measuring variability of the distribution of a quantitative variable. UNC-1.J.3 Standard deviation is a way to measure variability of the distribution of a quantitative variable. For a sample, the standard deviation is denoted by $s$: $s_x = \sqrt{\dfrac{1}{n-1}\sum(x_i - \bar{x})^2}$. The square of the sample standard deviation, $s^2$, is called the sample variance. UNC-1.J.4 Changing units of measurement affects the values of the calculated statistics.
	UNC-1.K Explain the selection of a particular measure of center and/or variability for describing a set of quantitative data. [Skill 4.B]	UNC-1.K.1 There are many methods for determining outliers. Two methods frequently used in this course are: UNC-1.K.1.i An outlier is a value greater than $1.5 \times \text{IQR}$ above the third quartile or more than $1.5 \times \text{IQR}$ below the first quartile. UNC-1.K.1.ii An outlier is a value located 2 or more standard deviations above, or below, the mean. UNC-1.K.2 The mean, standard deviation, and range are considered nonresistant (or non-robust) because they are influenced by outliers. The median and IQR are considered resistant (or robust), because outliers do not greatly (if at all) affect their value.

English	Русский
standard deviation/ˈstændəd ˌdiːvɪˈeɪʃn/	стандартное отклонение
variance/ˈveərɪəns/	дисперсией
five-number summary/faɪv ˈnʌmbə ˈsʌməri/	пятизначной сводки
percentile/pəˈsentaɪl/	перцентиль
cumulative relative frequency graph/ˈkjuːmjʊlətɪv ˈrelətɪv ˈfriːkwənsi ɡræf/	график кумулятивной относительной частоты

English	Русский
boxplot/ˈbɒksplɒt/	ящик с усами (бокс-плот)
normal distribution/ˈnɔːml ˌdɪstrɪˈbjuːʃn/	нормального распределения

Enduring Understanding	Learning Objective	Essential Knowledge
VAR-2 The normal distribution can be used to represent some population distributions.	VAR-2.A Compare a data distribution to the normal distribution model. [Skill 2.D]	VAR-2.A.1 A parameter is a numerical summary of a population. VAR-2.A.2 Some sets of data may be described as approximately normally distributed. A normal curve is mound-shaped and symmetric. The parameters of a normal distribution are the population mean, $\mu$, and the population standard deviation, $\sigma$. VAR-2.A.3 For a normal distribution, approximately 68% of the observations are within 1 standard deviation of the mean, approximately 95% of observations are within 2 standard deviations of the mean, and approximately 99.7% of observations are within 3 standard deviations of the mean. This is called the empirical rule. VAR-2.A.4 Many variables can be modeled by a normal distribution. Illustrative examples for VAR-2.A: Variables that can be modeled by a normal distribution: Body temperature Weight of a loaf of bread
	VAR-2.B Determine proportions and percentiles from a normal distribution. [Skill 3.A]	VAR-2.B.1 A standardized score for a particular data value is calculated as (data value − mean)/(standard deviation), and measures the number of standard deviations a data value falls above or below the mean. VAR-2.B.2 One example of a standardized score is a $z$-score, which is calculated as $z\text{-score} = \left(\dfrac{x_i - \mu}{\sigma}\right)$. A $z$-score measures how many standard deviations a data value is from the mean. VAR-2.B.3 Technology, such as a calculator, a standard normal table, or computer-generated output, can be used to find the proportion of data values located on a given interval of a normally distributed random variable. VAR-2.B.4 Given the area of a region under the graph of the normal distribution curve, it is possible to use technology, such as a calculator, a standard normal table, or computer-generated output, to estimate parameters for some populations.
	VAR-2.C Compare measures of relative position in data sets. [Skill 2.D]	VAR-2.C.1 Percentiles and $z$-scores may be used to compare relative positions of points within a data set or between data sets.

English	Русский
empirical rule/emˈpɪrɪkl ruːl/	эмпирическое правило
$z$-score/ˈzed skɔː/	$z$-балл (Z-score)

Введение в статистику: Что мы можем узнать из данных?

Язык вариации: Переменные

Категориальная или количественная?

Представление категориальной переменной с помощью таблиц

Представление категориальной переменной с помощью графиков

Покажите категориальную переменную в виде круговой диаграммы

Представление количественной переменной с помощью графиков

Исследуйте, как ширина интервала формирует гистограмму

Описание распределения количественной переменной

Сводная статистика для количественной переменной

Графические представления сводной статистики

Исследуйте пятичисловое описание как точечный график

Сравнение распределений количественной переменной

Сравните распределения с помощью точечных графиков

Нормальное распределение

Исследуйте площадь под нормальным распределением

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