# statistics

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## statistics

[stah-tis´tiks]
1. a collection of numerical data.
2. the mathematical science dealing with the collection, analysis, and interpretation of numerical data using the theory of probability, especially with methods for drawing inferences about characteristics of a population from examination of a random sample.
vital statistics data, usually collected by governmental bodies, detailing the rates of birth, death, disease, marriage, and divorce in a population.

## sta·tis·tics

(stă-tis'tiks),
1. A collection of numeric values, items of information, or other facts that are numerically grouped into definite classes and subject to analysis, particularly analysis of the probability that the resulting empiric findings are due to chance.
2. The science and art of collecting, summarizing, and analyzing data that are subject to random variation.

## statistics

/sta·tis·tics/ (stah-tis´tiks)
1. a collection of numerical data.
2. a discipline devoted to the collection, analysis, and interpretation of numerical data using the theory of probability.

vital statistics  data detailing the rates of birth, death, disease, marriage, and divorce in a population.

## statistics

[stətis′tiks]
a mathematic science concerned with measuring, classifying, and analyzing objective information.

## statistics

Statistics
1. A collection of datapoints or numerical values that can be categorized and subject to analysis; statistics are the raw material on which conclusions about cause-and-effect relationships are based.
2. The field that formally studies cause-and-effect relationships; the systematic collection, classification, and mathematical compilation of data vis-á-vis amount, range, frequency, or prevalence; those methods for planning experiments, obtaining data, and organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions. See Actuarial statistics, Coefficient of variation, Cusum statistics, Descriptive statistics, Health statistics, Mean, Standard deviation, t test.

## sta·tis·tics

(stă-tis'tiks)
1. A collection of numeric values, items of information, or other facts that are numerically grouped into definite classes and subject to analysis, particularly analysis of the probability that the resulting empiric findings are due to chance.
2. The science and art of collecting, summarizing, and analyzing data that are subject to random variation.

## statistics

See VITAL STATISTICS.

## sta·tis·tics

(stă-tis'tiks)
A collection of numeric values, items of information, or other facts numerically grouped into definite classes and subject to analysis, particularly of the probability that resulting empiric findings are due to chance.

## statistics,

n the branch of mathematics that gathers, arranges, condenses, coordinates, and mathematically manipulates obtained facts so that the numerical relationships between those facts may be seen clearly and freed from anomalies resulting from chance factors.
statistics, descriptive,
n.pl the statistics used to describe only the observed group or sample from which they were derived; summary statistics such as percent, averages, and measures of variability that are computed on a particular group of individuals.
statistics, inference,
n.pl the inferences made regarding characteristics or general principles about an unseen population based on the characteristics of the observed sample. Statistical findings from a sample are generalized to pertain to the entire population. The process of drawing inferences, making predictions, and testing significance are examples of inferential statistics.
statistics, nonparametric,
n.pl the sta-tistical methods used when the statistician cannot assume that the variable being studied is normally distributed in a population. Also called
distribution-free statistics.

## statistics

1. numerical facts pertaining to a particular subject or body of objects.
2. the science dealing with the collection, tabulation and analysis of numerical facts.

inferential statistics
conclusions, usually quantitative, drawn from an analysis of data.
salvage statistics
statistical technique used in an attempt to derive some useful information from a poorly designed or poorly executed experiment.
vital statistics
see vital statistics.

Q. What are the known statistics of Autism: Here is a question which needs a very detailed reply please. What are the known statistics of Autism: incidence, cost and ratio?

A. for more statistical information here are 2 sites:

and here is the CDC site link:

Q. Do you know if Propecia can truly stop hair loss and even grow back hair. do you have any statistics about it? do you know if there are any side effects to this medication?

A. it does work but there is some side affects, as in E.D. while you are on the med.

Q. What is the statistic number of women having breast cancer or under the threat of having breast cancer? where would i find a good , and reliable info about the disease ?

A. it is said that today 1 out of any 8 women will have breast cancer. there are also men who has breast cancer but the numbers are considerably lower.
about a good source of info- the site that doctoradhi gave you is pretty good, and you can use also the national medical library link:
http://www.nlm.nih.gov/medlineplus/breastcancer.html#cat22

good luck!

References in periodicals archive ?
Applied Statistics, Advanced Certificate The advanced certificate in applied statistics is designed for professionals who would like to concentrate on a subset of our courses and need those credentials in a shorter amount of time than it would take to finish an MS degree.
At the national level, Gionfriddo has worked extensively with the Agency for Healthcare Research and Quality on health services research dissemination to state and local policy leaders, helping to develop workshops and programs on long term care, prevention and public health, child health, minority health, and urban health, and was a member of the faculty of the Applied Statistics Training Institute of the National Center for Health Statistics.
of Toronto) introduce applied statistics and probability to undergraduate students in engineering and the natural sciences who are assumed to have had no previous exposure to probability and statistics.
Written for students and researchers in the fields of geology, biology, sociology and economics who need to employ stochastic models for applied statistics, this book covers survival analysis, hypothesis testing, regression, Markov chain Monte Carlo and Kernel density estimation.
Jennifer Priestley is a professor of applied statistics and directs Kennesaw's Center for Statistics and Analytical Services.
Ledford is a graduate of The University of Miami School of Business with a Master of Science in Applied Statistics and completed his undergraduate degree at Emory University with a Bachelor of Arts in Mathematics.
level work in finance and holds an MBA in finance and applied statistics from Rutgers University, an MS in information systems management from the New Jersey Institute of Technology, and a bachelor's degree in engineering from Bangalore University, India.
Independent research conducted by Eduventures on the Chicago market for master's degrees identified applied statistics as one of four critical areas of program development over the next decade, based on employment trends and student demand.
They should have a basic understanding of linear algebra; some previous exposure to probability distribution theory, and likelihood-based estimation and inference; and a working knowledge of applied statistics, especially analysis of variance and regression.
Extremely well illustrated and containing a wealth of real-life examples, this is intended for senior undergraduate and first level graduate students in generalized regression and can also be suitable in the study of applied statistics.
The Summit also features a preconference on Predictive Modeling Basics and Beyond by Ian Duncan, FSA, FIA, FCIA, MAAA, Visiting Associate Professor, Department of Probability and Applied Statistics, University of California Santa Barbara, and Founder, Solucia Consulting; as well as a postconference on Medicare Predictive Analytics that includes the following sessions:
Itkin holds a BA, and MA from the University of Illinois and is an ABD in applied statistics and quantitative methods.

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