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Related to Measures of central tendency: standard deviation, measures of dispersion


An arithmetic mean return of selected stocks intended to represent the behavior of the market or some component of it. One good example is the widely quoted Dow Jones Industrial Average, which adds the current prices of the 30 DJIA stocks, and divides the results by a predetermined number, the divisor.

Average (across-day) measures

An estimation of price that uses the average or representative price of a large number of trades.


A simple way to calculate the relative price of an index of stocks that involves adding the prices of all the stocks in the index and dividing by the total number of stocks. Market averages may be weighted, for example, for price or market capitalization. Movements in the market average of an index are considered a way to observe trends in the health of the companies represented in it. Some market averages are taken as an indicator of health in the broader economy; prominent examples of this include the Dow Jones Industrial Average and S&P 500 indices.


See averages.


A stock market average is a mathematical way of reporting the composite change in prices of the stocks that the average includes.

Each average is designed to reflect the general movement of the broad market or a certain segment of the market and often serves as a benchmark for the performance of individual stocks in its sphere.

A true average adds the prices of the stocks it covers and divides that amount by the number of stocks.

However, many averages are weighted, which usually means they count stocks with the largest market capitalizations more heavily than they do others. Weighting reflects the impact that the stocks of the biggest companies have on the markets and on the economy in general.

The Dow Jones Industrial Average (DJIA), which tracks the performance of 30 large-company stocks, is the most widely followed market average in the United States.

References in periodicals archive ?
responded to Terri's post by agreeing with her thought that the teaching of measures of central tendency should go beyond mere computation.
Based on the spatial distribution of ESP in the top three sampling increments in Figure 3 and the measures of central tendency from grid sampling in Table 3, it is unlikely that routine soil sampling that produces a composite sample from sub-samples taken in a zig-zag or grid pattern would have delineated these areas either.
He gives basic terminology and concepts such as scales of measurement and variables, then launches into a range of methods displaying data, measures of central tendency and variability, normal distribution, basic concepts of probability, sampling distributions and hypothesis testing, correlation, regression, multiple regression, power, the various analyses of variance, the chi-square, nonparametric and distribution-free statistical tests, and a very handy set of instructions on choosing the appropriate analysis.
The second chapter, "A Few Basics," explains introductory statistical methods such as measures of dispersion, measures of central tendency, and sampling.
Topics discussed are data analysis; measures of central tendency, dispersion, and position; probability; counting rules; normal and binomial distributions; and correlations.
Demonstrate the need for other measures of central tendency by pointing out the main weakness of the mean--the extent to which its value can be affected by extreme scores.
When measures of central tendency are needed, means are generally reported.
He works through statistical parameters in terms of the measures of central tendency and variation, standard scores, the z distribution, hypothesis testing, inferential statistics, including baloney detection, correlation and regression, the t test for independent and dependent groups, analysis of variance for a variety of situations, functional analysis of variance, nonparametric statistics and other statistical parameters and tests.
The authors cover measures of central tendency, correlation, regression, chi square test of significance, analysis of variance, group comparisons, and split block design.