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# the specific statistical methods that can be used to summarize or to describe a collection of data is called

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## The specific statistical methods that can be used to summarize or to describe a collection of data is called:

The specific statistical methods that can be used to summarize or to describe a collection of data is ... Analytical statistics d) All of the above ## The specific statistical methods that can be used to summarize or to describe a collection of data is called:

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## The specific statistical methods that can be used to summarize or

The specific statistical methods that can be used to summarize or to describe a collection of data is called: a Descriptive statistics b Inferential statistics c Analytical statistics d All of the above

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## The specific statistical methods that can be used to summarize or to describe a collection of data is called Descriptive statistics

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Which of the following is a statistical method of collecting secondary data?

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The data which the researcher collects during his research is called………. (pure statistics, systematic statistics)

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## Descriptive Statistics

Descriptive statistics is a set of brief descriptive coefficients that summarize a given data set representative of an entire or sample population. CORPORATE FINANCE FINANCIAL ANALYSIS

## Descriptive Statistics

By ADAM HAYES Updated August 01, 2022

Reviewed by THOMAS BROCK

Fact checked by MICHAEL LOGAN Investopedia / Jessica Olah

## What Are Descriptive Statistics?

Descriptive statistics are brief informational coefficients that summarize a given data set, which can be either a representation of the entire population or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread). Measures of central tendency include the mean, median, and mode, while measures of variability include standard deviation, variance, minimum and maximum variables, kurtosis, and skewness.

### KEY TAKEAWAYS

Descriptive statistics summarizes or describes the characteristics of a data set.

Descriptive statistics consists of three basic categories of measures: measures of central tendency, measures of variability (or spread), and frequency distribution.

Measures of central tendency describe the center of the data set (mean, median, mode).

Measures of variability describe the dispersion of the data set (variance, standard deviation).

Measures of frequency distribution describe the occurrence of data within the data set (count).

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## Understanding Descriptive Statistics

Descriptive statistics, in short, help describe and understand the features of a specific data set by giving short summaries about the sample and measures of the data. The most recognized types of descriptive statistics are measures of center: the mean, median, and mode, which are used at almost all levels of math and statistics. The mean, or the average, is calculated by adding all the figures within the data set and then dividing by the number of figures within the set.

For example, the sum of the following data set is 20: (2, 3, 4, 5, 6). The mean is 4 (20/5). The mode of a data set is the value appearing most often, and the median is the figure situated in the middle of the data set. It is the figure separating the higher figures from the lower figures within a data set. However, there are less common types of descriptive statistics that are still very important.

People use descriptive statistics to repurpose hard-to-understand quantitative insights across a large data set into bite-sized descriptions. A student's grade point average (GPA), for example, provides a good understanding of descriptive statistics. The idea of a GPA is that it takes data points from a wide range of exams, classes, and grades, and averages them together to provide a general understanding of a student's overall academic performance. A student's personal GPA reflects their mean academic performance.

Descriptive statistics, especially in fields such as medicine, often visually depict data using scatter plots, histograms, line graphs, or stem and leaf displays.

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## Types of Descriptive Statistics

All descriptive statistics are either measures of central tendency or measures of variability, also known as measures of dispersion.

### Central Tendency

Measures of central tendency focus on the average or middle values of data sets, whereas measures of variability focus on the dispersion of data. These two measures use graphs, tables and general discussions to help people understand the meaning of the analyzed data.

Measures of central tendency describe the center position of a distribution for a data set. A person analyzes the frequency of each data point in the distribution and describes it using the mean, median, or mode, which measures the most common patterns of the analyzed data set.

### Measures of Variability

Measures of variability (or the measures of spread) aid in analyzing how dispersed the distribution is for a set of data. For example, while the measures of central tendency may give a person the average of a data set, it does not describe how the data is distributed within the set.

So while the average of the data maybe 65 out of 100, there can still be data points at both 1 and 100. Measures of variability help communicate this by describing the shape and spread of the data set. Range, quartiles, absolute deviation, and variance are all examples of measures of variability.

Consider the following data set: 5, 19, 24, 62, 91, 100. The range of that data set is 95, which is calculated by subtracting the lowest number (5) in the data set from the highest (100).

### Distribution

Distribution (or frequency distribution) refers to the quantity of times a data point occurs. Alternatively, it is the measurement of a data point failing to occur. Consider a data set: male, male, female, female, female, other. The distribution of this data can be classified as:

The number of males in the data set is 2.

The number of females in the data set is 3.

The number of individuals identifying as other is 1.

The number of non-males is 4.

## Univariate vs. Bivariate

In descriptive statistics, univariate data analyzes only one variable. It is used to identify characteristics of a single trait and is not used to analyze any relationships or causations.

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