Consultation in data analysis

What is data analysis and why it is so important for us?

Data analysis is a crucial process in decision making for solving public and environmental health problem. With the existing of the data in the system and information technology, public health practitioner needs a clear understanding of the data analysis for measuring the performance and testing hypothesis related to the data obtained. In the practical world, everything has linked the graphics, statistics, and data and this analysis skill encourages the practitioner to dig deeper and ask more questions, improving their chance of making breakthrough discoveries in your data.

This skill of using the SPSS will let the researchers, making important discoveries of data analysis to a whole new level, letting the practitioner tackle routine and difficult statistical problems more easily and communicate your findings more effectively to the public domain and decision makers.


Step In Using Analytics For Your Research

Example of the steps that will be used in your scientific study can be summarized as follows:

  1. Define your variables
  2. Enter data
  3. Run frequency and descriptive analysis
  4. Data editing
  5. Reliability analysis
  6. Transformation of data
  7. Exploratory data analysis (EDA) dan normality assessment
  8. Data analysis for hypothesis testing

Services that you need

Our Services Which Includes but not limited to:

  1. Designing scientific study for Diploma, Bachelor, Master, and PhD
  2. Professional data analysis for clients
  3. Environmental forensics data analysis
  4. Descriptive and inferential statistic
  5. Regression and modeling technique
  6. Validation and reliability testing of instrumentation
  7. Environmental health training for professionals
  8. Occupational health training for professionals
  9. Online interactive learning system development and assessment

Your data will be our focus

We analyze your data using numerous software depends on your applications (SPSS, STATA, JMP, MS Excel or Freeware Analytical Software).

  • Descriptive analysis = frequency, percentages, mean ± s.d, Level, median, mode, IQR, range, and others
  • Reliability test = Cronbach Alpha, inter-rater correlation
  • Validity test / Factor Analysis = EFA and CFA, SEM AMOS
  • Normality test = Shapiro Wilk, Kolmogorov Smirnov, Histogram with normality curve, Q and Q plot, Boxplot, Skewness, and Kurtosis
  • Parametric test = t-test, ANOVA, Pearson Correlation, Regression, Simple Linear Regression, Multiple Linear Regression,
  • Non-parametric test = Mann Whitney U, Kruskal-Wallis, Kendal Tau and Spearman Correlation, Logistic Regression, Multiple Logistic Regression, Odd Ratio 95% CI.
  • Pre and Post-study = Pair t-test, Mc Necmar, Wilcoxon test
  • General Linear Model = Compare mean Repeated Measured
  • Agreement Analysis = Cohen Kappa
  • Mediator and Moderator analysis
  • Sensitivity and Specificity
  • Survival Analysis = Meire and Cox Regression (Medical Study)
  • Crosstab = Chi-Square, Yate Correction, Fisher Exact Test, Likelihood Ratio, Odd Ratio
  • Epidemiological estimates and risk measures
  • Scientific reports and thesis writing
  • Geospatial and temporal analysis (JMP and ArcGIS)
  • Course / Workshop / Tutorial in English and Bahasa Melayu medium
  • Data analysis using freeware (free software such as R-Statistics, Tanagra, Epi Info and others)
  • Courses on how to conduct scientific research easily and efficiently are available online
  • Other requirements and skills in scientific research required

Do you want to educate yourself? Join us

Mobile: 01129000345

Educational Consultant