The data that is collected needs to be arranged properly and any gaps in data must be found. The arrangement must be done cautiously, as even a single digit written wrongly will cause faulty results. The data can be qualitative or quantitative, depending on the research methodology that is being followed. Quantitative data refers to data collected from a large group and represented in figures. On the other hand, qualitative data is descriptive and subjective. It is mostly collected through interview sessions as well as personal observation. The representation of qualitative data is in text format. The data analysis chapter interprets both the qualitative and quantitative data. At MTD Data analysis, we ensure to offer our clients with the best dissertation writing assistance ranging from literature review, data analysis to creating the results and discussions chapter.

Qualitative data

Some of the more common statistical methods that we use are listed below.

Principal component analysis
Structural equation modeling
T-Test
Logistic Regression
Paired T-test
Chi-Square Test
ANOVA
ANCOVA
MANOVA
Repeated Measures ANOVA
Factor Analysis
Cluster Analysis

Linear Regression

Correlation
Mann-Whitney test
Kruskal-Wallis test

Wilcoxon Signed-Ranks test
McNemar's Test
Friedman's Test
Survival Analysis

You will realise there are many statistical software's for assisting you will analysis for either qualitative such as NVivo, ATLAS.ti, MAXQDA, Provalis Research Text Analytics Software, Quirkos, Dedoose, webQDA, HyperRESEARCH, Raven’s Eye, Qiqqa, Focuss On, Annotations, F4analyse, Datagrav, Interpris and your supervisor may or maynot recommend one of these.

For quantitative studies also there are a long list such as SPSS, matlab,Stata, SAS, R, minitab, JMP, PSPP, eviews etc
However you may opt for one or more depending on the type of analysis you want to perform.