Statistics Help

Managers apply statistical techniques virtually to every segment of an organization. Statistical techniques find application in our day to day life and also help organizations to take some of the most critical and crucial decisions every day. These techniques come handy where human brain cannot analyze or assimilate huge chunks of data and helps managers take decisions where there are multiple variables, huge amounts of data and close calls confront the decisions.

The statistical techniques are so diverse that statisticians commonly divide them into two broad categories:

An example of the same can be as follows:

Suppose a teacher computes an average grade for a psychology class. Teacher can be said to be using descriptive statistics when the statistics describe the performance of that one class and do not make any generalization about several classes. Graphs, Tables, and charts that display data to make it easier to understand are all examples of descriptive statistics.





Further, assume that the psychology teacher decides to use the average grade achieved by one psychology class to estimate the average grade achieved in all five sections of the same psychology course. The question of estimating this average grade will be a problem that would come under the purview of inferential statistics. Some people also refer to this as statistical inference.

A thesis would normally require conducting both descriptive and inferential statistics. However, there is no thumb rule. It might be prudent on various occasions to seek Statistical Help for Thesis in case the researcher is unsure of what would entail in the statistical part of the PhD Thesis.

Quantitative analysis for thesis or the statistical help required to complete thesis work must be comprehensive and should ensure a sound and thorough understanding of the methods used by the researcher. Quantitative analysis for thesis deals with the work related to analyzing the numeric data collected through primary or secondary sources. Our Statistics Help for thesis service is unique and covers the following working:

  • Grouping and displaying data.
  • Measures of central tendency and dispersion in frequency in frequency distributions
  • Probability Distributions
  • Sampling and Sampling Distributions.
  • Hypothesis testing
  • Sample tests
  • Analysis of Variance (ANOVA) and Chi-Square tests
  • Regression and Correlation.
  • Multiple regressions and modelling.
  • Non parametric methods
  • Time series and forecasting
  • Multivariate data analysis

What is a Multivariate Analysis?

Multivariate analysis refers to all statistical techniques that simultaneously analyze multiple measurements on individuals or subject under consideration. In a world with increasing complexities on a daily basis, business is also becoming more and more dynamic and the number of factors that any business decision would take into consideration is also on a rise. Given these conditions, the use and importance of multivariate techniques has also risen significantly and therefore are being used frequently. As such, simultaneous analysis of more than two variables can be considered multivariate analysis.

Various types of Multivariate techniques can be:

  • Principal component and common factor analysis
  • Multiple regression and multiple correlation
  • Multiple discriminant analysis and logistic regression
  • Conjoint analysis
  • Cluster analysis
  • Canonical correlation analysis
  • Structural equation modeling
  • Multi-dimensional scaling.

Our expert statisticians have completed various statistics consultation projects, which involved the use of software including SPSS, SPSS AMOS, Stata, Statistica, R, E-Views, SAS, Minitab and Excel.

Whether you need assistance in developing the right questionnaire or choosing the right scale, Chanakya Research offers smart, quick and reliable solutions with explanations to these problems. We also help our clients comprehend the rationale as to why a particular method is used for analyzing a particular data set. A typical statistical consultation program would include:

  • Data Entry
  • Data Management techniques
  • Questionnaire design
  • Validity and Reliability tests
  • Statistical testing
  • Output explanation
  • Interpretation report
  • Results and discussion chapter writing

Contact us to get more information on statistical assistance.



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