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Practical Guide to Conducting Fieldwork in Kenya: Lessons from Regional Immersion and Survey Realities.

Highlights Most researchers design surveys with ideal conditions in mind; but the realities of Kenyan fieldwork can make or break the integrity of your data. Recently, I immersed myself across Kenya’s diverse regions to uncover the true operational challenges behind social and market research. From sparse populations at the Coast to household overlaps in Western Kenya, I dissected the myths, examined proven methodologies, and revealed why adaptive protocols—not rigid designs—are the real driver of reliable insights, efficiency, and long-term impact. Inside this article, you’ll discover: • The critical distinction between research design and field realities (and why most studies miss it) • Region-specific budgeting strategies that keep surveys feasible and cost-effective • Practical methodologies to optimize enumerator KPIs and reduce fatigue across diverse terrains • Real-world lessons from extensive immersion that show what works—and what doesn’t—in Kenyan surveys ...
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Employee Satisfaction, Engagement?

Highlights Employee Engagement: The Hidden Key to Business Prosperity Most leaders confuse employee satisfaction with employee engagement; but the difference could make or break your company’s future. Recently, I sat down with a fellow researcher to dissect this very issue. Together, we pulled apart the myths, examined proven methodologies, and revealed why engagement, not satisfaction, is the true driver of growth, innovation, and long-term success. Inside this article, you’ll discover: • The critical distinction between satisfaction and engagement (and why most companies get it wrong) • Research-backed methods to measure engagement with precision • Practical strategies to transform engagement into measurable business prosperity • Real-world insights from two experienced researchers who’ve seen what works, and what doesn’t This isn’t just theory. It’s a roadmap for leaders and researchers who want to unlock higher productivity, stronger retention, and a thriving workplace cul...
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Big Data and Market Research Synergy

Highlights Recently I introduced this topic to my fellow consultants, and it instantly elicited a mixed reaction. I remember issues of bank halls and how retail bankers already apply the concept of customer data to predict needs and customer perceptions or expectations of their services. in this new article, and inspired by perspectives of other researchers, I present how big data can compliment market research. Download the article at affordable price, $5.05. All payments on my blog are maintained and processed by PayPal. PayPal terms of payment, therefore apply. Visit the PayPal website for more on their terms of payment. For any problems with auto-downloads of the article after paying, please contact me at omondisammy@outlook.com, I will get back ASAP. My blog does not store your credit card information
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Tips for Qualitative Data Analysis: Transcript Coding

Highlights Data Coding is a key step in qualitative data analysis. The best approach to qualitative coding is simple, straightforward, and free. Whether inductive or Deductive, your coding takes place in five basic steps, that I have explicitly explained in this article. These steps can be followed by anyone who has an interview transcript, to come up with a robust analysis. Whether its your first time analyzing qualitative data or you are an M&E lead overseing qualitative data analysis, these simple steps, and consequent ethical considerations will see you through your analysis and by extention, compliance. Download the article at affordable price, $4.05. All payments on my blog are maintained and processed by PayPal. PayPal terms of payment, therefore apply. Visit the PayPal website for more on their terms of payment. For any problems with auto-downloads of the article after paying, please contact me at omondisammy@outlook.com, I will get back ASAP. My blog does not store ...
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Inferential Statistics: Focus on P Value Part II

Key Highlights Knowing that P value is greatly limited or bounded on the fact that: P value by itself fails to provide a good measure of evidence as regards a hypothesis or a model. P values have the potential to measure the incompatibility of data relative to a statistical model specified. P value fails to measure the probability that the hypothesis under scrutiny is true or the probability that data was a result of pure randomness. The statistical significance of the P value is short of explaining the effect size. Why do we have everyone reporting statistical significance only based on P value, even for such important studies as Biomedical trials? Find out the reason and what to do to report results comprehenssively in the second series of Focus on P value for just $4.
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Saving Resources through Sound GBV Screening: A Community Member Observation of GBV Screening by a CDC and PEPFAR Funded Program in Remote Counties of Kenya.

Abstract One of the key indicators monitored by programs implementing the PEPFAR-funded projects is school-based HIV and violence prevention. To prioritize this key performance indicator for the program, a vulnerability assessment is conducted through data collection on variables that build up gender-based violence; physical violence, emotional violence, and sexual violence among the AGYWs enrolled in these programs. Once a target priority is enumerated, GBV screening is conducted by a trained HTS provider. Wouldn’t the fund attain a more targeted and effective use if the vulnerability assessment data at enrollment was consistent with the GBV screening results? It is a postulation of this study that the data to support this claim as maintained by the program will reveal a great disparity and inconsistency because the enrollment data is blatant miss information when screening for GBV and the gap is in the manner of its collection, the point in time it is collected, the consultants tem...
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Emerging Data Management Trends

Key Highlights Gain competitive edge by abandoning old Data management strategies slowing you down. This article is a guide towards reorganizing your data science department to take early lead in data processes for 2023 and beyond. Crafted in a simple and concise vocabulary while maintaining in-depth research into the industry's most current trends, this article is a must read not only for data professionals but all that fancy emerging issues. From Data Centers in Africa to Information Technology decision maker survey in the U.S, recent trends in Data Management are revamping data strategies and shrinking the old ways of data management for better and more dynamic data processing. This article stipulates why you should look at the most current data management trends before implementing a data management strategy, and how a specific approach applies to your particular needs. What is the impact of ML on the Risk analysis department of a financial services center? How much o...
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