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Statistics Assignment, Homework Help

Statistics: - Though for a layman the term ‘Statistics’ may mean data of some sort, it has a much broader meaning. Statistics is a kind of research methodology, which deals with collection, analysis, interpretation and presentation of data. It is applicable to a wide variety of academic disciplines, from natural and social sciences to humanities, government and business. Statistics plays a very vital role in the formulation of economic plans, estimation of industrial demand and sales figures, maintenance of the quality of products and minimization of inspection costs, forecasting agricultural production and helping studies in the field of genetics. Thus a Statistician is well versed in statistical methods and its applications. The numerous applications of Statistics make its knowledge indispensable.

There are many statistical tools and techniques, one being Descriptive statistics. Descriptive Statistics deals with the methods of organization, reduction, summarization and presentation of data in order to make them amenable to rational analysis and interpretations. The level of complexity of statistical problems varies. It may range from computation of simple measures like mean, median and mode to computation of standard regression results and complicated forecasts using time series data. Across all colleges students are often tested on these topics.

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Tutors at www.theglobaltutors.com are well qualified and experienced. All Statistics tutors hold at least a Masters Degree in Statistics and are from the best Institutes. Tutors are capable of handling all kinds of problem related to statistics. Our statistics tutors can also help in assignments involving use of different software like MINITAB, MATLAB, SPSS, STATA, E-Views, R etc.

Some topics relating to statistics assignment help and statistics homework help provided bTabular and Diagrammatic Presentation of frequency and non-frequency data

Measures of Central Tendency

Dispersion

Skewness and Kurtosis

Probability of an event

Conditional Probability

Independence of events

Discrete and Continuous Probability Distributions and their properties

Regression Analysis

Correlation Analysis (Including Rank correlations)

Random sample generation

Computation of expectation and standard error

Point and Interval Estimation of Parameters

Maximum Likelihood Estimation

Testing of Hypothesis

Power and Confidence Intervals

Non-parametric Tests

Contingency tables and Chi-square Test

Analysis of Variance (ANOVA)

Design of Experiments

Sample Surveys

Time Series Analysis and Forecasting

Scaling of Scores and Ratings

Z-Scores

T-scores

Principal Components

Factor Analysis

Cluster Analysis

Discrimination and Classification