- Dissertation Writing
- PhD Thesis
- MBA projects
- Medical Dissertation
- Journal Publication support
- Editing and Proof Reading
- Statistics help
- Assignment writing
- Essay writing
- Research Proposal
- Dissertation Abstract
- Dissertation Introduction
- Dissertation Literature Review
- Research Methodology
- Results/Statistical analysis
- Questionnaire development
- References / Bibliography
SPSS is an important tool for any statistical analysis. Dissertations often require this tool for the completion of research using statistical data’s. Spss full help is provided to researchers in the course of their study and result analysis. We make sure that you get the exact and most accurate results with the latest versions of Tools that we use like Spss, SAS in the statistical data analysis.
Spss is gaining its importance because it’s easy to use and is flexible to perform statistical tests. When you are here with us with your research paper, we teach you the importance and necessity of using Spss tool in your research. We give you enormous amount of examples to make you understand the use of various tools as used in your dissertations to help you better.
We perform following analysis:
- Exploratory analysis – To check normality [Kolmogorov Smirnov test], outliers, mean, standard deviation, standard error of mean, kurtosis, skew ness, minimum. Maximum, standard deviation, confidence interval,.
- Correlation test [Bivariate: Pearson correlation, spearman rank, Kendall’s Tau, simple scatter plot, partial correlation]
- Chi-square analysis
- Reliability analysis – Cronbach’s alpha, etc.
- Time series analysis
- Regression, multiple regression, logistic regression
- T-test, Analysis of Variance (ANOVA), Analysis of covariance (ANCOVA), , General Liner Model (GLM), Repeated measure design,
- Non-parametric Test: Wilcoxon Signed Rank Test, The Kruskal Wallis Test, Mann-Whitney Test, Multivariate Analysis of variance (MANOVA)
- Forecasting analysis [manpower planning techniques, sales, etc.]
- Confirmatory Factor analysis
- Discriminatory analysis
- Factor analysis
- Structural Equation Model [SEM]
- Neural Network
- Decision Tree analysis
- Marketing analysis Techniques
- Perceptual Mapping
- To reveal possible errors in the data, e.g. outliers.
- To reveal features of the dataset, e.g. symmetry, skew, scatter.
- To test for a normal distribution.
- To determine whether parametric or non-parametric tests should be used.
- Much of statistics is about detecting patterns - something which the human eye and brain are very good at. EDA shows you the patterns which are hidden when the data is in numerical form.
Analyze, Descriptive statistics, frequencies, select the variable
Many statistical procedures for quantitative data are less reliable when the distribution of data values is markedly non-normal, Sometimes, a transformation of the variable can bring the distribution of values closer to normal. But clearly document what transoformation have made Eg. Calculating logarithm. But clearly document what transoformation have made.
Statistical Analysis System [SAS] is an intergrated system of software products that enables you to perform
1. Data entry, retrival and management
2. Report writing and graphics
3. Statistical and mathematical analysis
4. Business planning, forecasting and decision support
5. operation research and project management
6. Quality improvement
7. Application development
At TutorsIndia we guide you to solve your analysis using SAS programming techniques.