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How to use Stata for Data Analysis
Stata Programming Assignment Help Services
Being an online platform, here are some of the services we provide;
Reading and adding data into software
Performing statistical tests – these could include simple computations, inferential statistics and descriptive statistics.
Interpretation of the results – This can be quite challenging especially if one is not careful. You may perform the right statistical test but end up giving misleading interpretation. It is therefore for this reason that you need our Help
Reporting the data analysis results – Data analysis is only a piece of the cake in a report. Our experts can complete reports where the data analysis is done using software.
Solving Stata related assignments
Help you understanding the software – we can help you where you may be not understand about the software
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Stata is a statistical software that is used for data analysis all over the world which is built on a select and click interface. The advantage of using the software is that it generates calculations and graphs automatically allowing the user to focus on interpretation of the results.
Data Analysis Using Stata
Some of the key features of the software are;
Basic statistics – The main objective of Stata is to conduct statistical analysis. Some of the basic statistics that can be performed by the software include descriptive statistics, one and two sample tests, one and two proportion tests, one and two variance tests, correlation and covariance tests, normality tests and Poisson goodness-of-fit test.
Graphical analysis – Visual representation of data is one useful aspect of statistics. Such graphs include scatterplots, matrix plots, histograms, line and bar graphs, probability and probability distribution plots, pie charts etc. can be automatically generated
Regression is another main feature. The types of regression analysis that can be performed by the user include linear and non-linear regression, binary, ordinal and nominal logistic regression, partial least squares, Poisson regression and orthogonal regression amongst others
Analysis of Variance – These include ANOVA, ANCOVA MANOVA, MANCOVA general linear models, response prediction and optimization, analysis of means amongst many others.
Other features include design of experiments analysis, power and sample size analysis, quality tools analysis, survival analysis, Time series analysis and non-parametric tests such as Wilcoxon test.