Statistics (from German: Statistik, orig. "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). Descriptive statistics are most often concerned with two sets of properties of a distribution (sample or population): central tendency (or location) seeks to characterize the distribution's central or typical value, while dispersion (or variability) characterizes the extent to which members of the distribution depart from its center and each other. Inferences on mathematical statistics are made under the framework of probability theory, which deals with the analysis of random phenomena. A standard statistical procedure involves the collection of data leading to a test of the relationship between two statistical data sets, or a data set and synthetic data drawn from an idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis of no relationship between two data sets. Rejecting or disproving the null hypothesis is done using statistical tests that quantify the sense in which the null can be proven false, given the data that are used in the test. Working from a null hypothesis, two basic forms of error are recognized: Type I errors (null hypothesis is falsely rejected giving a "false positive") and Type II errors (null hypothesis fails to be rejected and an actual relationship between populations is missed giving a "false negative"). Multiple problems have come to be associated with this framework, ranging from obtaining a sufficient sample size to specifying an adequate null hypothesis. Measurement processes that generate statistical data are also subject to error. Many of these errors are classified as random (noise) or systematic (bias), but other types of errors (e.g., blunder, such as when an analyst reports incorrect units) can also occur. The presence of missing data or censoring may result in biased estimates and specific techniques have been developed to address these problems. (Wikipedia).

Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

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From playlist Statistics (Full Length Videos)

Statistics - The vocabulary of statistics

This video will give show you a few terms that are used in statistics such as data, population, sample, parameter, statistic, and variable. Remember that it matters if you are talking about the whole group, or a portion of that group. For more videos please visit http://www.mysecretmatht

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Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Introduction to Statistics - Quantitative Data versus Qualitative Data

From playlist Statistics

This branch of math can help you to organize and interpret information. It’s used in a variety of fields, and it has many applications in daily life. To learn more basic concepts in #statistics, check out the free tutorial on our website: https://edu.gcfglobal.org/en/statistics-basic-conce

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Lecture01 Introduction to this course on medical statistics

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This lecturelet will introduce you to the series on statistical analyses of time-frequency data. For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/

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From playlist From Numbers to Variables to Data in Statistics (WK 1 - QBA 237)

Statistical questions | Data and statistics | 6th grade | Khan Academy

What makes a question a "statistical question"? Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6-statistical-questions/e/statistical-questions?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade

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MountainWest RubyConf 2015 - Learning Statistics Will Save Your Life

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