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Nigeria's free digital learning hub. Videos, lecture notes, practice questions and leaderboards aligned with CCMAS, NBTE, NCCE, WAEC, NECO, IJMB and JAMB curricula.
Public Health · 200 Level
This is the complete lecture note for PHS 202 Biostatistics, prepared for Public Health students at 200 Level. You can read it online below, open it in the full viewer, or download the PDF for offline study. It pairs with the course's video lectures, so you can read and watch together.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS COURSE CODE: PHS 202 COURSE TITLE: Biostatistics COURSE CREDIT LOAD: (2 Units C: LH 30) LISTS OF SERIES: • Series 1: The Role of Statistics in Health Sciences and Data Description • Series 2: Probability Concepts and Random Variables • Series 3: Statistical Distributions and Their Applications • Series 4: Estimation, Confidence Intervals, and Hypothesis Testing • Series 5: Contingency Tables, Regression, Variance Analysis, and Study Design Outline for Series 1 Main Parts and Sub-Parts 1.1 The role of statistics in health sciences • 1.1.1 Importance of statistics in health research • 1.1.2 Applications of statistics in decision-making and policy • 1.1.3 Limitations of statistics in health sciences 1.2 Types and sources of data in health sciences • 1.2.1 Primary and secondary data • 1.2.2 Quantitative and qualitative data • 1.2.3 Data collection methods in health studies 1.3 Data description and presentation • 1.3.1 Frequency distributions and tables • 1.3.2 Graphical presentation of data (charts, histograms, etc.) • 1.3.3 Measures of central tendency (mean, median, mode) • 1.3.4 Measures of dispersion (range, variance, standard deviation) 1.4 Introduction to statistical thinking in health sciences • 1.4.1 Concept of variability in health data • 1.4.2 Importance of summarising and interpreting data • 1.4.3 Linking descriptive statistics to further statistical analysis
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Introduction Statistics play a central role in the health sciences because they provide the tools needed to collect, analyse, and interpret data in a meaningful way. Imagine a hospital trying to determine whether a new treatment is effective: without statistics, decisions would rely on guesswork rather than evidence. By learning how statistics are applied in health research, you will be better equipped to evaluate findings, design studies, and make informed decisions that can improve patient outcomes and public health policies. The aim of this Series is to introduce you to the role of statistics in health sciences and to equip you with the skills to describe and present data effectively. We shall commence this Series by examining the role of statistics in health sciences, focusing on its importance, applications, and limitations. Next, we will explore the types and sources of data, distinguishing between primary and secondary data, as well as quantitative and qualitative forms. Following that, we will move on to data description and presentation, where we will study frequency tables, charts, measures of central tendency, and measures of dispersion. Finally, we will wrap up by considering statistical thinking in health sciences, highlighting variability, the importance of summarising data, and how descriptive statistics link to further analysis. Series Learning Outcomes Upon completing this Series, you should be able to: • SLO 1.1 define the role of statistics in health sciences and explain its importance in research and decision-making, • SLO 1.2 identify and classify different types and sources of data used in health studies, • SLO 1.3 demonstrate how to describe and present data using frequency tables, charts, and measures of central tendency, • SLO 1.4 calculate and interpret measures of dispersion such as range, variance, and standard deviation, and • SLO 1.5 analyse the concept of variability in health data and evaluate how descriptive statistics support further statistical analysis. 1.1 The Role Of Statistics In Health Sciences 1.1.1 Importance of statistics in health research Statistics is the science of collecting, analysing, and interpreting data. In health sciences, it provides the foundation for evidence-based practice. For example, when researchers test whether a new drug reduces blood pressure, they rely on statistical methods to determine if the observed changes are genuine or due to chance. Statistics also helps in summarising large amounts of data into meaningful information that can guide clinical decisions and public health policies. Fill in the blank: The science of collecting, analysing, and interpreting data is called ______.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Diagram showing the role of statistics in health research, linking data collection, analysis, and interpretation to decision-making. Caption: Figure 1.1 Role of statistics in health sciences 1.1.2 Applications of statistics in decision-making and policy Statistics is widely applied in health decision-making. Hospitals use it to monitor patient outcomes, governments rely on it to design vaccination programmes, and researchers apply it to evaluate risk factors for diseases. By analysing data, health professionals can identify trends, predict outcomes, and allocate resources more effectively. Fill in the blank: Hospitals use statistics to monitor ______ outcomes.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Box 1.1 Selected applications of statistics in health sciences Content: • Monitoring patient outcomes • Designing vaccination programmes • Evaluating risk factors for diseases • Allocating health resources 1.1.3 Limitations of statistics in health sciences While statistics is powerful, it has limitations. Poorly collected data can lead to misleading results, and incorrect application of statistical methods may produce invalid conclusions. Moreover, statistics cannot replace clinical judgement; it only supports it. Therefore, health
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS professionals must use statistics carefully, ensuring that data is reliable and methods are appropriate. Fill in the blank: Poorly collected ______ can lead to misleading results. Diagram showing limitations of statistics, such as poor data quality, misuse of methods, and reliance on clinical judgement. Caption: Figure 1.2 Limitations of statistics in health sciences Pilot questions 1.1 1. Define statistics in the context of health sciences. 2. State two reasons why statistics is important in health research. 3. Give two examples of how statistics is applied in health decision-making.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS 4. What is one limitation of statistics in health sciences? 5. Why must health professionals use statistics carefully? 1.2 Types And Sources Of Data In Health Sciences 1.2.1 Primary and secondary data Primary data refers to information collected directly from the source for a specific study. Examples include patient interviews, laboratory test results, and clinical observations. This type of data is often more reliable because it is tailored to the research question, but it can be time-consuming and costly to obtain. Secondary data refers to information that has already been collected by others and is available for use. Examples include hospital records, census data, and published research articles. Secondary data is easier to access and less expensive, but it may not always fit the exact needs of a study. Fill in the blank: Information collected directly from the source for a specific study is called ______ data.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Diagram comparing primary and secondary data with examples. Caption: Figure 1.3 Primary and secondary data in health sciences 1.2.2 Quantitative and qualitative data Quantitative data refers to information that can be measured and expressed numerically, such as blood pressure readings, age, or weight. It allows for statistical analysis and comparison across groups. Qualitative data refers to descriptive information that captures experiences, opinions, or behaviours, such as patient feedback, interview transcripts, or case notes. It provides depth and context but is not easily reduced to numbers. Fill in the blank: Information that captures experiences and opinions is called ______ data.
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