Rohitah International is a leading professional firm with the specialization in Health and IT research. Data management is one of the core activities of Rohitah. Data management through Excel and SPSS is core training program being conducted by Rohitah. Our portfolio encompasses the training for Individual, Group and Corporate sector. We are truly devoted to our students to groom their knowledge in data management through Excel and SPSS and help them to reach on the top of the ladder.

The courses at Rohitah are general purpose courses targeting with the elementary knowledge of data management for Agriculture, Economics, Food Security, and Livelihoods, Nutrition, Education, Medical or public health professionals but wish to be conversant with the advanced concepts and applications of data management. The training is designed for participants who are reasonably proficient in English

After completing the courses from Rohitah, The students can make an immense contribution to strengthening and improving the data management of the health/hospital, education, agriculture and related sectors in India as well as at the international level. The studies of Rohitah will make a phenomenal difference and paradigm shift in effective data management in their respective sector.

Developing technical and theoretical data management related IT based skills at various levels in public health, including NGO’s and related organisations, is an important mission of Rohitah International. Therefore, the courses and teaching pedagogy are designed specifically keeping in mind the requirement of Officials, NGOs and researchers working at different levels in India and other countries in all over the world. 

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Data Management through Excel (Basic)

This course is mainly aimed at professionals working in NGO/Research segment who have, or will soon have, responsibility for managing and manipulating data using MS Excel on a day to day basis.  The course assumes elementary knowledge, begins with an introduction to the Excel environment and ends with participants being skilled in using MS Excel functions, Chart, advanced data management utilities

Participants are expected to possess basic knowledge of Windows environment and must be familiar with using personal computers for some of their routine office tasks.

Topics covered in this course will be Understand the basics of Excel, Understand Excel Ribbon, Prepare and format Excel sheets as per requirement, create and explore charts and graphs, Using Formulas and functions, working with page layouts and cell properties, Printing, and publishing documents.

The course is aimed at analysts who are beginning to use Excel for tasks such as basic data management, summarizing data (using basic functions and formulas), producing charts, or basic statistical analysis. The course will also be useful for anyone who is self-taught and looking to fill any gaps in their knowledge. The course focuses on the practical application of Excel for data management and is suitable for those with limited or no prior experience of using Excel.

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Advanced Data Management through Excel (Advance)

This course is mainly designed for early career researchers including postdoctoral researchers, doctoral candidates, State and District level health personnel working in public, NGOs, private sector health care organisations and institutions. This is a general course targeting participants with elementary knowledge of Statistics from Agriculture, Education, Medical or public health professionals.

This advanced course covers the concepts and techniques concerning Data Management, Organizing  data from various sources , Connect data from different sources (eg: MS-Access, Text File, CSV File, SQL Server, ODBC etc), Data Analysis , Data Validation, Summarize the Reports, Dashboard Report, MIS Report , Charts ,  Protect a workbook and save with a backup , Understand and use advanced functions , Consolidate data, link and export data, Use of What-If Analysis tools  PivotTables and Pivot Charts , Create and modify Microsoft Excel Macros.

Participants will be exposed to these topics and how each applies to and can be used in their respective business environment. Analyzing Data with Excel shows you how to solve real-world problems by taking Excel's data analysis features to the max. Rather than focusing on individual Excel functions and features. This hands-on training course targets specific situations and then demonstrates how to develop spreadsheets for these problem areas. This course is recommended for end users seeking proficiency in the use of Excel at an advanced level.

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Data Management through SPSS (Basic)

SPSS is among the most widely used programs for statistical analysis in social science. It is also widely used by market researchers, health researchers, survey companies, governments, education researchers and marketing organizations. It is a statistical analysis package and so allows any organization or individual that holds large amounts of data to analyze it and understand it more deeply.

This course is for beginners so developed considering hands-on including lots of small exercises and examples to ensure that you spend time working with SPSS. We believe that data management skills that are developed in this way are deeper than those developed from theoretical explanations. Our exercises are carefully designed to emphasize the key aspects of the respective domain,  the participant is being worked.

Topics covered in this course will be Introduction to SPSS, Sources and organisation of data, Reading Data Using the Data Editor, Working with Multiple Data Sources, Examining Summary Statistics for Individual Variables, Modifying Data Values,  Cross-tabulation Tables, Working with Output, Creating and Editing Charts and pivot tables, Working with SPSS Syntax, Multiple Response Variables, Using Numeric Functions, System Variables, Computing Date, Time and String variables. The course also covers Helpful SPSS features for Data Management like Identify duplicates cases, Custom Attributes, Variables sets, Aggregating Data, Merging Files by Adding cases / Adding variables and Deploying SPSS Results

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Advanced Data Management through SPSS (Advance)

Anyone who has worked with SPSS and wants to explore additional data management and manipulation features of SPSS may join this course. The course is a natural follow-on to the Advance course or as a standalone for experienced users who have learned the operations of SPSS on their own.

In this Course, you will consider in depth some of the more advanced statistical procedures that are available in SPSS. You'll take a look at several advanced statistical techniques and discuss situations when each may be used, the assumptions made by each method, how to set up the analysis using SPSS and how to interpret the results.

We are aware that SPSS is among the most widely used programs for statistical analysis in social science. It is also widely used by market researchers, health researchers, survey companies, governments, education researchers and marketing organizations. Statistics like Cross tabulation, Frequencies Descriptive Ratio Statistics, Means, t-test, ANOVA, Correlation (bivariate, partial, distances), nonparametric tests, Linear regression Factor analysis, cluster analysis (two-step, K-means, hierarchical and many features of SPSS are accessible via GUI menus or can be programmed by SPSS syntax files.

This course Demonstrates an understanding and skills associated with data extraction, data management and Statistical analysis. The course introduces the steps of data analysis and how To prepare the coding plan and create the dataset. Setting up a data entry page, Working with variables, Adding, moving and recoding of variables, Central Tendency & Dispersion, Summarising Data, The Output Viewer, Modifying Data Values, Making Interference about Population from Samples, Checking the Form of Distributions, Analysing Combinations of Categorical & Continuous Data using t-tests, Testing Relationship between Categorical variables, Analysing Combination of Continuous variables using Correlations, Editing Charts are the key highlights of this course.


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