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DEFINITION OF STATISTICS
"Statistics" is the branch of mathematics which is concerned with the collection and analysis of large quantities of numerical 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 assignment experts use information gained from analyzing large quantities of raw data to forecast and predict facts that can impact humans in extraordinary ways.
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STATISTICS ASSIGNMENT HELP FOR COLLEGE STUDENTS
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College statistics is not as easy as it sounds - collecting, analysing and classifying data to make predictions and inferences.
These days, statistics involves deploying complex processes to collect, analyse, interpret and present the facts collected to the respective audiences in plain language.
Students learn this subject, both as a major or as an elective subject. In both cases, you will have to write and submit often complex statistics assignments or dissertations.
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SOME IMPORTANT STATISTICS ASSIGNMENT HELP TOPICS:
Deterministic mathematical and statistical modelling of within-host HIV dynamics
Tests of association and linkage in family studies
Models for survival data with cure rate
Bayesian networks for analysis of micro-array expression data
On-line quality control
Methods for quantitative trait loci (QTL) mapping
Identification of protein-coding gene regions using hidden Markov models
Chaos in population dynamics
Survival analysis with correlated data
Semiparametric transformation models for analysis of censored survival data
Joint modeling of longitudinal and time-to-event (survival) data
Nonstationary covariance models for spatial analysis
Use of the propensity score for estimating causal treatment effects in observational studies
Analysis of interval-censored survival data
Null models of biodiversity
Hierarchical Bayesian models for spatial data
Robust design of industrial experiments
Multiple imputation methods for analysis of missing data
Analysis of longitudinal binary data using generalized estimating equations
Regression models for the analysis of current status data
Evaluation of diagnostic tests and Receiver Operating Characteristic curves
Design and analysis of phase I clinical trials
Modeling of financial derivatives
Analysis of longitudinal data in the presence of informative (nonignorable) dropout
Analysis of dispersion effects
Methods for the design and analysis of group sequential clinical trials
IMPORTANT STATISTICS ASSIGNMENT HELP TOPICS
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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.
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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 email@example.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 assignment help to college and university students worldwide. We work on advanced as well as elementary Matlab programming assignment topics. Contact us today for expert help with your Matlab homework help. Matlab is owned by a company called Mathworks. Check Matlab Programming Assignment 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 assignment 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 assignment help for college and university students. Let our experts do your SAS 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 assignment problems using R. Contact us today-chat with our customer success team on our website or email us at firstname.lastname@example.org.
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 assignments for college and university students. Contact us for 100% personalized GRETL assignment 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 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 email@example.com for immediate Eviews assignment help.
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Business Statistics Assignment help
We provide help with business statistics homework. Business statistics is the branch of statistics which applies the principles of statistics in business where it is used for financial analysis, market research, production, auditing and operations. Business statistics can also be further classified into
Descriptive statistics allows you to summarize large sets of numerical data. It includes topics such as Mean, Medial & Mode, Central Tendency, Statistical Dispersion etc. In other words, Descriptive statistic allows you to analyze, present and describe data in a meaningful way so that patterns can be obseved. Descriptive statistics can be classified into:
Measure of central tendency, including mean, median and mode &
Measure of spread, which includes range, quartiles, absolute deviation, variance and standard deviation.
Sampling is an important part of Inferential statistics. And Inferential statistics allows you to draw inferences about the population from where samples were obtained. There are two methods of inferential statistics:
Estimation of parameters
Testing of statistical hypotheses
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Limitations of Statistics:
Statistics only deal with aggregate of facts. In other words, it does not deal with a sigle item or phenomena.
Satistics can only study numeric or quantitative subjects
Statistics is not accurate - because it is only an aggregate of facts.
Statistics is just one of the many methods available to study a phenomenon or problem. Other methods should also be adequately deployed to get accurate results.
Statistics is prone to be misused and misinterpreted. It has to be used by experts only.
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