Examples of descriptive statistics in the following topics:

 Contrast descriptive and inferential statistics
Descriptive statistics and inferential statistics are both important components of statistics when learning about a population.
 Descriptive statistics are distinguished from inferential statistics in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent.
 Descriptive statistics provides simple summaries about the sample.
 Descriptive statistics is the discipline of quantitatively describing the main features of a collection of data, or the quantitative description itself.
 Descriptive statistics are distinguished from inferential statistics in that descriptive statistics aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent.
 descriptive statistics (noun) A branch of mathematics dealing with summarization and description of collections of data sets, including the concepts of arithmetic mean, median, and mode.
 inferential statistics (noun) A branch of mathematics that involves drawing conclusions about a population based on sample data drawn from it.

 Learning Objectives
1.Define "descriptive statistics"
2.
 Distinguish between descriptive statistics and inferential statistics
Descriptive statistics are numbers that are used to summarize and describe data.
 Descriptive statistics are just descriptive.
 Here we focus on (mere) descriptive statistics.
 Some descriptive statistics are shown in Table 1.

 Assess the significance of descriptive statistics given its limitations
Descriptive statistics can be manipulated in many ways that can be misleading, including the changing of scale and statistical bias.
 Descriptive statistics is a powerful form of research because it collects and summarizes vast amounts of data and information in a manageable and organized manner.
 Descriptive statistics, however, lacks the ability to identify the cause behind the phenomenon, correlate (associate) data, account for randomness, or provide statistical calculations that can lead to hypothesis or theories of populations studied.
 Descriptive statistics can be manipulated in many ways that can be misleading.
 Bias is another common distortion in the field of descriptive statistics.
 descriptive statistics (noun) A branch of mathematics dealing with summarization and description of collections of data sets, including the concepts of arithmetic mean, median, and mode.
 null hypothesis (noun) A hypothesis set up to be refuted in order to support an alternative hypothesis; presumed true until statistical evidence in the form of a hypothesis test indicates otherwise.

 This area of statistics is called "Descriptive Statistics".

 This is called descriptive statistics .
 Descriptive statistics and analysis of the new data tend to provide more information as to the truth of the proposition.
 In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount as simply as possible.
 This data can then be subjected to statistical analysis, serving two related purposes: description and inference.
 Descriptive statistics summarize the population data by describing what was observed in the sample numerically or graphically.
 sample (noun) a subset of a population selected for measurement, observation, or questioning to provide statistical information about the population

 Since qualitative data represent individual categories, calculating descriptive statistics is limited.
 Statistics that describe or summarize can be produced for quantitative data and to a lesser extent for qualitative data.
 Therefore, all descriptive statistics can be calculated using quantitative data.
 As qualitative data represent individual (mutually exclusive) categories, the descriptive statistics that can be calculated are limited, as many of these techniques require numeric values which can be logically ordered from lowest to highest and which express a count.
 descriptive statistics (noun) A branch of mathematics dealing with summarization and description of collections of data sets, including the concepts of arithmetic mean, median, and mode.

 Statistics is generally broken down into two categories: descriptive statistics and inferential statistics.
 In short, statistics is the study of data.
 It includes descriptive statistics (the study of methods and tools for collecting data, and mathematical models to describe and interpret data) and inferential statistics (the systems and techniques for making probabilitybased decisions and accurate predictions based on incomplete data).
 Statistics itself also provides tools for predicting and forecasting the use of data and statistical models.
 In this book, AlKindi provides a detailed description of how to use statistics and frequency analysis to decipher encrypted messages.
 statistics (noun) a mathematical science concerned with data collection, presentation, analysis, and interpretation

 With this example, you have begun your study of statistics.
 Organizing and summarizing data is called descriptive statistics.
 The formal methods are called inferential statistics.
 Statistical inference uses probability to determine how confident we can be that the conclusions are correct.
 If you can thoroughly grasp the basics of statistics, you can be more confident in the decisions you make in life.

 Recall that the field of Statistics involves using samples to make inferences about populations and describing how variables relate to each other.
 Descriptive statistics summarizes the population data by describing what was observed in the sample numerically or graphically.
 This data can then be subjected to statistical analysis, serving two related purposes: description and inference.
 Descriptive statistics summarizes the population data by describing what was observed in the sample numerically or graphically.
 Probability is used in "mathematical statistics" (alternatively, "statistical theory") to study the sampling distributions of sample statistics and, more generally, the properties of statistical procedures.
 sample (noun) a subset of a population selected for measurement, observation, or questioning to provide statistical information about the population

 Explain the significance of valid models in statistical inference
A statistical model is a set of assumptions concerning the generation of the observed data and similar data.
 Any statistical inference requires assumptions.
 Descriptions of statistical models usually emphasize the role of population quantities of interest, about which we wish to draw inference.
 Descriptive statistics are typically used as a preliminary step before more formal inferences are drawn.
 Incorrect assumptions of simple random sampling can invalidate statistical inference.