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Statistics can be defined in many ways.

It is the branch of mathematics which is concerned with the collection and analysis of large quantities of numeric data in order to draw inferences based on probability.

It is derived from the Latin word "status" which means "group or numbers" of figures that represent certain facts which are of interest to human beings.

Large quantities of data are mathematically analysed so that the knowledge gained from it can be of benefit to human society. Statistics homework solvers use information gained from analysing large quantities of raw data to forecast and predict facts that can impact human beings in extraordinary ways.

Statistics is also studied as Business Statistics, Biostatistics, Biomathematics, Bioinformatics, Environmental Statistics, Industrial Statistics, Mathematical Statistics, Statistical Genetics and Social Statistics.


Statistics and probability are two completely different subjects of study. Though they are contextually related, they are not the same. Probability is nothing but the 'chance' of something happening. Like when you flip a coin, what is the chance of you getting a head or a tail? Let us call probability as 'the study of chance'. You can define the probability formula as the ratio of the favorable outcomes to the total number of possibile outcomes. You can compute the probability of an event as follows: If P(A) > P(B), the probability of event A or just P(A) to happen is more likely. But if they are the same, as in P(A) = P(B), then both events A and B have equal chances to happen. Linking a table or equation to each of the outcomes of a statistical experiment gives you what is known as 'probability distribution'. An event with a higher probability is more likely to occur as against an event with lesser probability. Statistics, on the other hand, deals with collecting, analyzing huge volumes of numeric data and extracting inferences out of it. Statistical techniques are used in almost industries for various purposes.

Importance of statistics

Statistics lets you collect, analyze large quantities of data (of just information) and draw inferences out of it. In other words, when you analyze (or study) large amounts of data, you will be in a better positon to make certain predictions, based on your statistical study. If statistical techniques are used in the right manner, you can expect correct inferences or predictions and results. However, statistics is one of the most misused branches of study, with some statisticians often drawing conclusions that may not be accurate. When used correctly, you get vital insights into your data and you can use it for the welfare of the society. There are two major statistical techniques - descriptive statistics and inferential statistics. Descriptive statistics summarizes data from a sample by using indexes (eg. mean, standard deviation), whereas, inferential statistics draws conclusions from data using random variation.


Statistics help for college students provided by us is holistic and splits complex statistical problems into smaller and better manageable chunks of information.

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Business statistics too has two categories - descriptive and inferential. Business statistics deals with the business related aspects of statistics. Businesses and professionals use business statistics concepts to take crucial decisions to improve the quality of their products and services. Business statistics allows them to understand, infer and predict factors that are important to them.

According to Wikipedia, Business Statistics is

"the science of good decision making, in the face of uncertainitity...".
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For those who are good at math - calculus and differential equations and the like, getting through the Elementary Statistics course should be easy.

Students have a lot of questions about elementary statistics - is there a difference between just 'statistics' and 'elementary statistics'?

How is elementary statistics used in other domains like psychology, probability etc?

Is it any different from modern elementary statistics?

How do you define an 'elementary unit' and 'elementary event' in statistics?

And many more questions like that. In fact, you will have to pass a paper in elementary statistics in order to qualify for certain majors. So, this is one subject you will need to score well.

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In Statistics, Probability is defined as the chances or likelyhood of an event happening in a random experiment. Probability is measured on a scale of 0 (zero) to 1 where 0 indicates the event might never happen and 1 indicating a strong probability that the event will happen.

Probability theory can also be defined as the branch of mathematics that analyses random events. The result of a random event cannot be predicted before the event itself occurs and the final outcome is determined by chance.

Regression analysis in statistics is used to analyze the relationship between variables using a set of statistical processes. This is especially used in Statistical modelling and studies the relationship between a dependent variable (also known as the 'criterion variable') and one or more independent variables, also referred to as 'predictors'. Regression statistics helps us to understand changes in the value of the dependent variable when the value of one of the independent variables is changed and that of another independent variable is left unchanged.

In statistics, ANOVA is the acronym for 'Analysis of Variance'. As a student of statistics, there are many important terms you need to be familar with, with respect to ANOVA like: ANOVA test, one way ANOVA, two way ANOVA, MANOVA, Factorial ANOVA, Comparision between ANOVA and T-test, Repeated measures ANOVA. You will also need to familiarize yourself with how to run an ANOVA.

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A distribution function is also known as 'cumulative distributive function' or 'CDF'. Sometimes, it is also referred to as 'cumulative density function'. The CDF of a random variable X or more simply, 'the distribution function' of of X evaluated at x is the probability that X will assume a value less than or equal to x.

Our Statistics homework experts are thoroughly familiar with all aspects of distribution functions in statistics and will provide accurate solutions to your statistics problems.

A Random Variable, X, in statistics ia a variable whose possible values are the results of any random phenomenon. Random variables are of two types: discrete random variable and continuous random variable. Example of a random variable is the tossing of a coin, which can only have one of the two values - heads or tails.

The Pearson's Chi Square Test in statistics is also known as 'goodness of fit statistic'. It also indicates how much the the likelyhood of an observed distribution is due to chance.

The Binomial distribution is used as the basis for the well-known Binomial test of statistical importance.

A Binomial distribution with parameters n & p, can be defined as the discrete probability distribution of the number of successes in a range of independent experiments, n, with each asking a "yes-no" question and each with its own boolean outcome-a random variable with a single bit of information such as success/yes/true/one (with probability p) or failure/no/false/zero (with probability q-1-p).

Bernoulli Process: When you run the experiment for one single success/failure outcome, it is called Bernoulli experiment and the outcomes are known as Bernoulli Processes. Which means, for a single single trial, n=1, the Binomial Distribution is the Bernoulli Distribution.

Poisson Distribution is a statistical tool used in probability theory that predicts the probability of an event or multiple events happening when the frequency of occurrence of that event is already known. In other words, a Poisson distribution lets us know the probability of a sequence of events taking place in any fixed interval of time and space.

A Normal Distribution is also known as the Bell Curve. Other bell-shaped distributions incude the Cauchy Distribution, Student's T distribution and the Logistic distribution. The Normal Distribution is extensively used in statistics, business organizations and government offices. Normal Distribution is also known as the Gaussian or Laplace-Gauss or just Gauss distribution.

Data Analysis, in statistics is the process of "cleaning up, modifying and modelling data" in order to discover useful information, conclusions and assist in decision making. There are a number of methods and techniques for data analysis in statistics, each being used for a specific purpose in business, science and social science.

Business Intelligence is used by organizations to help with their strategic and operational decision making processes like product positioning, pricing and marketing decisions. Business Intelligence helps businesses to gain valuable insights into their own as well as competitor strategies, get information about new markets, check market demand and conditions for products and services for different market categories and analyze impact of marketing efforts and resources. Business Intelligence involves handling and analyzing huge amounts of data and generate valuable business that businesses use in a number of ways. According to Wikipedia, Business Intelligence provides "historical, current and predictive information" about business operations and consists of strategies and technologies used by business organizations for the analysis of large volumes of data. Business Intelligence is often abbreviated as just BI.

SPSS is the short form for "Statistical Package for Social Sciences". SPSS is one of the most popular statistical softwares and is currently known as IBM SPSS after IBM took over the parent company in 2009. SPSS has come a long way since its introduction into the market in 1968. Our experts provide elementary and advanced homework help for SPSS assignments. Follow the link for more information: We do SPSS homework.

Minitab is another popular statistical software, widely used for a number of statistical analysis with which companies can focus their resources and efforts on those areas where they have the most impact. Minitab offers a free 30 day trial period. Our statistics experts are extensively trained in Minitab and have intricate knowledge of the many features of this software. We are available 24/7-chat with us on our website any time of the night or day or drop us an email at info@urgenthomeworkhelp.com for 100% personalized Minitab homework help.

Matlab is a highly advanced engineering software and comes with strong statistical analysis capabilities thanks to it's statistics toolbox and econometrics toolbox. Matlab is not a simple menu driven software, instead engineers have to learn the Matlab programming language in order to leverage its strengths to the maximum. Our experts offer Matlab programming homework help to college and university students worldwide. We work on advanced as well as elementary Matlab programming homework topics. Contact us today for expert help with your Matlab homework help. Matlab is owned by a company called Mathworks. Check Matlab Programming Homework Help for more information.

Stata is a data analysis and statistical software which provides a complete, integrated environment that provides everything you could possibly need for effective data analysis, data management and graphics. Using Stata, you can carry out hundreds of different kinds of statistical analysis and get accurate results. Connect with us any time for advanced help with your Stata homework assignment. We guarantee top results, 24/7 support online and assured, on-time delivery.

SAS is another widely used software for statistical analysis. It offers great features for analytics, business intelligence and data management which helps companies to take business-critical decisions. We offer advanced SAS homework help for college and university students. Let our experts do your SAS homework assignments and be assured of top grades and delivery on time. We are open 24/7.

R language is a free statistical programming language which provides an ideal software environment for statistical computing and graphics. R language is also easy to learn and comes packed with many powerful features. Our experts can solve complex statistical homework and assignment problems using R. Contact us today-chat with our customer success team on our website or email us at info@urgenthomeworkhelp.com.

GRETL is another great statistical software. GRETL is an acronym for Gnu Regression Econometrics and Time-series Library. As is evident from its name, GRETL is used for a number of statistical analysis, mostly concerned with econometrics. Gretl is free and open-source. We do GRETL homework & assignments for college and university students. Contact us for 100% personalized GRETL homework help with assured scores.

Eviews is a powerful statistical software that is used mostly for time-series related econometric analysis. This software is MS Windows-based and offers researchers, business organizations and government organizations access to advanced forecasting and modelling tools. Initially developed by a company called QMS (Quantitative Micro SOftware), Eviews is now a part of IHS Markit Ltd. Contact us for help with your Eviews homework assignments. No matter how complex your assignment questions are, our experts can solve it accurately and provide expert solutions. We work 24/7. Chat with us any time or email us at info@urgenthomeworkhelp.com for immediate Eviews homework help.


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statistics homework help


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Statistics deals with the theories and practice of collecting and analyzing data and making inferences from the observations.

Statistics also allows you to organize and present your data.

The principles of statistics are often used to a solve certain social, scientific or industrial problem or get more information about a certain population.

Statistics helps scientists and researchers to study, understand trends and make predictions based on existing information.

The study of statistics allows scientists to compare multiple sets of data and look for trends and variation and then arrive at meaningful conclusions. Given the huge amount of data at our disposal these days, it is important to have a good understanding of statistical methods and tools in order to properly use this data.

In spite of its uses in many fields, there are also certain limitations in statistics.

  1. Laws of statistics are good only on average.
  2. Statistics can only be applied to homogenous data and not to heterogeneous data.
  3. Statistics can only be applied to numeric or quatitative data.
  4. Adequate care has to be exercised while collecting and interpreting data, else we may not get accurate results.
  5. Statistics does not apply to individual items as it is only an "aggregate of facts".
Unless handled professionally and ethically, statistical readings can be easily manipulated and/or misinterpreted.

That is why there is this famous saying "there are three types of lies: lies, damned lies and statistics"!

In spite of this, statistics remains one of the most important branches of study worldwide.

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