Contents

- 1 Thủ Thuật về Is a branch of science which đơn hàng with the collection presentation analysis and information quantitative data? Chi Tiết
- 2 Descriptive statistics
- 3 Tabular methods
- 4 Graphical methods
- 4.1 Is a branch of science that đơn hàng with the collection organization analysis of data and drawing of inferences from the samples to the whole population?
- 4.2 What is a branch of mathematics that đơn hàng with collection analysis interpretation and presentation of data?
- 4.3 What is the branch of science that đơn hàng with the systematic collection of data?
- 4.4 Which studies the collection analysis interpretation or presentation of data?
- 4.5 What is the branch of science researchers use to analyze data?
- 4.6 Video Is a branch of science which đơn hàng with the collection presentation analysis and information quantitative data? ?
- 4.7 Share Link Download Is a branch of science which đơn hàng with the collection presentation analysis and information quantitative data? miễn phí

## Thủ Thuật về Is a branch of science which đơn hàng with the collection presentation analysis and information quantitative data? Chi Tiết

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- Read a brief summary of this topic Descriptive statisticsTabular methodsGraphical methodsIs a branch of science that đơn hàng with the collection organization analysis of data and drawing of inferences from the samples to the whole population?What is a branch of mathematics that đơn hàng with collection analysis interpretation and presentation of data?What is the branch of science that đơn hàng with the systematic collection of data?Which studies the collection analysis interpretation or presentation of data?What is the branch of science researchers use to analyze data?

### Read a brief summary of this topic

**statistics**, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data

as well as information about a variety of economic activities provided much of the early impetus for the field of statistics. Currently the need to turn the large amounts of data available in many applied fields into useful information has stimulated both theoretical and practical developments in statistics.

Data are the facts and

figures that are collected, analyzed, and summarized for presentation and interpretation. Data may be classified as either quantitative or qualitative. Quantitative data measure either how much or how many of something, and qualitative data provide labels, or names, for categories of like items. For example, suppose that a particular study is interested in characteristics such as age, gender, marital status, and annual income for a sample

of 100 individuals. These characteristics would be called the variables of the study, and data values for each of the variables would be associated with each individual. Thus, the data values of 28, male, single, and $30,000 would be recorded for a 28-year-old single male

with an annual income of $30,000. With 100 individuals and 4 variables, the data set would have 100 × 4 = 400 items. In this example, age and annual income are quantitative variables; the corresponding data values indicate how many years and how much money for each individual. Gender and marital status are qualitative variables. The labels male and female provide the qualitative data for gender, and the labels single, married, divorced, and widowed indicate marital status.

Sample survey methods are used to collect data from observational studies, and experimental design methods are used to collect data from experimental studies. The area of descriptive statistics is concerned primarily with methods of presenting and interpreting data using graphs, tables, and numerical summaries. Whenever statisticians use data from a sample—i.e., a subset of the population—to make statements about a population, they are performing

statistical inference. Estimation and hypothesis testing are procedures used to make statistical inferences. Fields such as health care,

biology, chemistry, physics, education, engineering, business, and economics make extensive use of statistical

inference.

Methods of probability were developed initially for the analysis of gambling games. Probability plays a key role in statistical inference; it is used to provide

measures of the quality and precision of the inferences. Many of the methods of statistical inference are described in this article. Some of these methods are used primarily for single-variable studies, while others, such as regression and correlation analysis, are used to make inferences about relationships among two or more

variables.

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## Descriptive statistics

Descriptive statistics are tabular, graphical, and numerical summaries of data. The purpose of descriptive statistics is to facilitate the presentation and interpretation of data. Most of the statistical presentations appearing in newspapers and magazines are descriptive in nature. Univariate methods of descriptive statistics use data to enhance the understanding of a single variable; multivariate methods focus on using statistics to understand the relationships among two or more

variables. To illustrate methods of descriptive statistics, the previous example in which data were collected on the age, gender, marital status, and annual income of 100 individuals will be examined.

## Tabular methods

The most commonly used tabular summary of data for a single variable is a

frequency distribution. A frequency distribution shows the number of data values in each of several nonoverlapping classes. Another tabular summary, called a relative frequency distribution, shows the fraction, or percentage, of data values in each class. The most common tabular

summary of data for two variables is a cross tabulation, a two-variable analogue of a frequency distribution.

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For a qualitative variable, a frequency distribution shows the number of data values in each qualitative category. For instance, the variable gender has two categories: male and female. Thus, a frequency distribution for gender would have two nonoverlapping classes to show the number of males and females. A relative

frequency distribution for this variable would show the fraction of individuals that are male and the fraction of individuals that are female.

Constructing a frequency distribution for a quantitative variable requires more care in defining the classes and the division points between adjacent classes. For instance, if the age data of

the example above ranged from 22 to 78 years, the following six nonoverlapping classes could be used: 20–29, 30–39, 40–49, 50–59, 60–69, and 70–79. A frequency distribution would show the number of data values in each of these classes, and a relative frequency distribution would show the fraction of data values in each.

A cross tabulation is a two-way table with the rows of the table representing the classes of one variable and the columns of the

table representing the classes of another variable. To construct a cross tabulation using the variables gender and age, gender could be shown with two rows, male and female, and age could be shown with six columns corresponding to the age classes 20–29, 30–39, 40–49, 50–59, 60–69, and 70–79. The entry in each cell of the table would specify the number of data values with the gender given by the row heading and the age given by the column heading. Such a cross tabulation could be helpful in

understanding the relationship between gender and age.

## Graphical methods

A number of graphical methods are available for describing data. A bar graph is a graphical device for depicting

qualitative data that have been summarized in a frequency distribution. Labels for the categories of the qualitative variable are shown on the horizontal axis of the graph. A bar above each label is constructed such that the height of each bar is proportional to the number of data values in the category. A bar graph of the marital status for the 100 individuals in the above example is shown in Figure 1. There are 4 bars in the graph, one for each

class. A pie chart is another graphical device for summarizing qualitative data. The size of each slice of the pie is proportional to the number of data values in the corresponding class. A pie chart for the marital status of the 100 individuals is shown in

Figure 2.

A histogram is the most common graphical presentation of quantitative data that have been summarized in a frequency distribution. The values of the quantitative variable are shown on

the horizontal axis. A rectangle is drawn above each class such that the base of the rectangle is equal to the width of the class interval and its height is proportional to the number of data values in the class.

### Is a branch of science that đơn hàng with the collection organization analysis of data and drawing of inferences from the samples to the whole population?

Statistics is a branch of applied mathematics that involves the collection, description, analysis, and inference of conclusions from quantitative data. The mathematical theories behind statistics rely heavily on differential and integral calculus, linear algebra, and probability theory.

### What is a branch of mathematics that đơn hàng with collection analysis interpretation and presentation of data?

Statistics is the branch of mathematics that studies the collection, organization, analysis and interpretation of numerical data.

### What is the branch of science that đơn hàng with the systematic collection of data?

Statistics is the branch of mathematics that đơn hàng with the collection, organization, analysis, and interpretation of numerical .

### Which studies the collection analysis interpretation or presentation of data?

A branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data is called statistics.

### What is the branch of science researchers use to analyze data?

Statistics is a branch of science that đơn hàng with collection, organization and analysis of data from the sample to the whole population.

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