Descriptive Statistics - Tables, Graphs & Descriptive Statistics Review

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Flashcards covering core concepts from the lecture notes on descriptive statistics, including charts, tables, and interpretations of various graphical methods.

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28 Terms

1
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What is Descriptive Statistics?

A set of methods that summarize and describe the properties of a data set, providing a basic step for understanding data before detailed analysis.

2
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Name some graphical methods commonly used for descriptive statistics.

Frequency distribution tables, bar charts, pie charts, box plots, stem-and-leaf plots, histograms, scatter plots, and parallel coordinates plots.

3
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What are the numerical measures of central tendency?

Mean, median, and mode.

4
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What are the measures of dispersion?

Range, interquartile range (IQR), variance, standard deviation, and coefficient of variation.

5
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What is a frequency distribution?

A table that groups data by category or class and shows the frequency (count) for each category or class.

6
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In a frequency distribution for categorical data, what are the two main columns?

Categories (values) in the first column and their frequencies in the second column.

7
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What is a class interval?

A numeric data range divided into equal-width intervals used to organize numeric data.

8
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What is a class mark?

The representative value of a class interval, usually the interval midpoint.

9
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What is relative frequency?

Frequency divided by the total number of observations.

10
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What is cumulative frequency?

The running total of frequencies up to and including a given class.

11
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What is cumulative relative frequency?

Cumulative frequency divided by the total number of observations.

12
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What is a histogram?

A graph of numeric data using a frequency distribution with adjacent bars for continuous data.

13
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What is the difference between a histogram and a bar chart?

Histograms are for numeric data with continuous intervals and bars that touch; bar charts are for categorical data with separated bars.

14
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What does skewness indicate in a histogram?

The direction of the tail: right (positive skew, tail to the right) or left (negative skew, tail to the left).

15
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What is a stem-and-leaf plot?

A data display that preserves original values by splitting numbers into stems and leaves and ordering the leaves.

16
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What is an ogive?

A cumulative frequency curve, representing cumulative frequencies against the data values.

17
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What is a five-number summary?

Minimum, first quartile (Q1), median, third quartile (Q3), and maximum.

18
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What is a box plot?

A graphical representation of the five-number summary: a box from Q1 to Q3, a line for the median, whiskers to min and max (often within 1.5 IQR), and outliers.

19
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What is an outlier?

An observation that is unusually far from the rest of the data; may indicate data entry or measurement error or a true extreme value and requires careful handling.

20
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What is a time series plot?

A plot of observations over time with time on the x-axis and the variable on the y-axis.

21
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What is a scatter plot used for?

Displays the relationship between two numeric variables and indicates linearity and direction (positive or negative) of the relationship.

22
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What is a scatter plot matrix?

A grid showing all pairwise scatter plots for three or more variables, used to explore relationships.

23
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What is a parallel coordinates plot?

A multivariate plot where each variable has a parallel axis; data points are connected across axes to reveal patterns or clusters.

24
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What is a mosaic plot?

A graphical display for contingency tables using rectangular areas proportional to category frequencies, allowing comparisons across multiple categorical variables.

25
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What is a contingency table?

A cross-tabulation of two or more categorical variables showing their joint distribution.

26
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What is aspect ratio in graphs?

The ratio of the x-axis length to the y-axis length; affects how the graph’s shape and relationships are visually perceived.

27
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Give an example of a class interval for body weight data.

50–60 kg, 60–70 kg, 70–80 kg, etc.

28
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Why is data visualization important?

It helps quickly understand data characteristics, facilitates initial exploration, and supports informed decision-making.