What is 'Statistics'
Statistics is a form of mathematical analysis that uses quantified models, representations and synopses for a given set of experimental data or reallife studies. Statistics studies methodologies to gather, review, analyze and draw conclusions from data. Some statistical measures include mean, regression analysis, skewness, kurtosis, variance and analysis of variance.
BREAKING DOWN 'Statistics'
Statistics is a term used to summarize a process that an analyst uses to characterize a data set. If the data set depends on a sample of a larger population, then the analyst can develop interpretations about the population primarily based on the statistical outcomes from the sample. Statistical analysis involves the process of gathering and evaluating data and then summarizing the data into a mathematical form.
Statistical methods analyze large volumes of data and their properties. Statistics is used in various disciplines such as psychology, business, physical and social sciences, humanities, government and manufacturing. Statistical data is gathered using a sample procedure or other method. Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.
Mean
A mean is the mathematical average of a group of two or more numerals. The mean for a specified set of numbers can be computed in multiple ways, including the arithmetic mean, which shows how well a specific commodity performs over time, and the geometric mean, which shows the performance results of an investor’s portfolio invested in that same commodity over the same period.
Regression Analysis
Regression analysis determines the extent to which specific factors such as interest rates, the price of a product or service, or particular industries or sectors influence the price fluctuations of an asset. This is depicted in the form of a straight line called linear regression.
Skewness
Skewness describes the degree a set of data varies from the standard distribution in a set of statistical data. Most data sets, including commodity returns and stock prices, have either positive skew, a curve skewed toward the left of the data average, or negative skew, a curve skewed toward the right of the data average.
Kurtosis
Kurtosis measures whether the data are lighttailed (less outlierprone) or heavytailed (more outlierprone) than the normal distribution. Data sets with high kurtosis have heavy tails, or outliers, which implies greater investment risk in the form of occasional wild returns. Data sets with low kurtosis have light tails, or lack of outliers, which implies lesser investment risk.
Variance
Variance is a measurement of the span of numbers in a data set. The variance measures the distance each number in the set is from the mean. Variance can help determine the risk an investor might accept when buying an investment.
Analysis of Variance
Ronald Fisher developed the analysis of variance method. It is used to decide the effect solitary variables have on a variable that is dependent. It may be used to compare the performance of different stocks over time.

Variance
Variance is the spread between numbers in a data set and their ... 
Descriptive Statistics
Descriptive statistics is a set of brief descriptive coefficients ... 
Normal Distribution
A probability distribution that plots all of its values in a ... 
Variability
The extent to which data points in a statistical distribution ... 
Excess Kurtosis
Excess kurtosis describes a probability distribution with fat ... 
Portfolio Variance
Portfolio variance is the measurement of how the actual returns ...

Trading
Trading with Gaussian models of statistics
The study of statistics originated from Carl Friedrich Gauss and helps us understand markets, prices and probabilities, among other applications. 
Investing
What's Skewness?
Skewness describes how a data distribution leans. 
Insights
SKEW Index Suggests a Market Downturn is Possible
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Investing
Calculating volatility: A simplified approach
Though most investors use standard deviation to determine volatility, there's an easier and more accurate way of doing it: the historical method. 
Trading
Exploring the Exponentially Weighted Moving Average
Learn how to calculate a metric that improves on simple variance. 
Insights
Can Investors Trust Official Statistics?
The official statistics in some countries need to be taken with a grain of salt. Find out why you should be skeptical. 
Insights
World Bank Data For Dummies
Developing countries can't always afford to track the data crucial to setting the right economic policies and programs. That's where the World Bank steps in. 
Small Business
Calculating (Small) Company Credit Risk
Determining creditworthiness of smaller and mediumsized corporations isn't as easy as for larger companies, but these tips can help. 
Investing
Optimize your portfolio using normal distribution
Normal or bell curve distribution can be used in portfolio theory to help portfolio managers maximize return and minimize risk.

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