Nigeria's free digital learning hub. Videos, lecture notes, practice questions and leaderboards aligned with CCMAS, NBTE, NCCE, WAEC, NECO, IJMB and JAMB curricula.
Loading
Nigeria's free digital learning hub. Videos, lecture notes, practice questions and leaderboards aligned with CCMAS, NBTE, NCCE, WAEC, NECO, IJMB and JAMB curricula.
Environmental Health Science · 200 Level
This is the complete lecture note for EHS212 BIOSTATISTICS, prepared for Environmental Health Science 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: EHS 212 COURSE TITLE: Biostatistics COURSE UNIT LOAD: (2 Units C: LH 30) SERIES LIST 1. Series 1: Fundamentals of Statistics and Data 2. Series 2: Sampling Techniques and Data Distribution 3. Series 3: Descriptive and Inferential Statistics 4. Series 4: Vital and Health Statistics in Environmental Health 5. Series 5: Statistical Packages and Calculation of Rates Suggested Outline – Series 1: Fundamentals of Statistics and Data Part 1.1 Definition and Scope of Statistics • 1.1.1 Definition of Statistic, Statistics, and Data • 1.1.2 Importance of statistics in environmental health research • 1.1.3 Distinction between descriptive and inferential statistics Part 1.2 Types and Classification of Data • 1.2.1 Qualitative and quantitative data • 1.2.2 Primary and secondary data • 1.2.3 Levels of measurement: nominal, ordinal, interval, ratio Part 1.3 Measures of Central Tendency • 1.3.1 Definition and purpose of central tendency • 1.3.2 Mean, median, and mode with examples • 1.3.3 Applications of central tendency in health research Part 1.4 Data Collection and Presentation • 1.4.1 Methods of data collection in health research • 1.4.2 Tools and techniques for presenting data (tables, charts, graphs) • 1.4.3 Importance of accurate presentation for decision-making
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Introduction – Series 1: Fundamentals of Statistics and Data Background Statistics is a vital tool in environmental health research. It provides methods for collecting, organising, analysing, and interpreting data. By learning the fundamentals of statistics and data, students gain the ability to describe health problems accurately and make evidence-based decisions. This Series introduces the basic concepts of statistics, types and classification of data, measures of central tendency, and methods of data collection and presentation. Aim The aim of this Series is to equip learners with foundational knowledge of statistics and data. It will enable them to define key terms, classify data appropriately, apply measures of central tendency, and present data effectively in health research contexts. Sequential synopsis • Part 1.1 defines statistics, statistics, and data, and explains their scope and importance in environmental health. • Part 1.2 explores types and classifications of data, including qualitative, quantitative, primary, secondary, and levels of measurement. • Part 1.3 introduces measures of central tendency, explaining mean, median, and mode with examples. • Part 1.4 discusses methods of data collection and presentation, highlighting tools such as tables, charts, and graphs. Series Learning Outcomes – Series 1: Fundamentals of Statistics and Data By the end of this Series, learners should be able to: • SLO 1.1: Define the terms Statistic, Statistics, and Data, and explain their scope and importance in environmental health research. • SLO 1.2: Classify types of data, distinguishing between qualitative and quantitative, primary and secondary, and levels of measurement. • SLO 1.3: Illustrate and calculate measures of central tendency, including mean, median, and mode, with examples relevant to health research. • SLO 1.4: Describe and apply different methods of data collection and present data effectively using tables, charts, and graphs. 1.1 Definition and Scope of Statistics 1.1.1 Definition of Statistic, Statistics, and Data A Statistic is a single numerical value that summarises or describes a characteristic of a sample, for example, the average age of students in a class. Statistics refers to the
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS science and methods of collecting, organising, analysing, and interpreting data. Data are raw facts, figures, or observations collected for analysis. Fill in the blank: A single numerical value that summarises a characteristic of a sample is called a ______. Figure 1.1 Placeholder: Diagram showing the relationship between data, statistics, and statistic. Caption: Relationship between data, statistics, and statistic. 1.1.2 Importance of Statistics in Environmental Health Research Statistics is important in environmental health because it helps: • To describe health problems accurately. • To identify patterns and trends in disease occurrence. • To evaluate interventions and policies. • To support evidence-based decision making. Fill in the blank: Statistics helps to identify patterns and trends in ______ occurrence.
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Box 1.1 Placeholder: Text box listing the importance of statistics in environmental health research. Caption: Importance of statistics in environmental health. 1.1.3 Distinction between Descriptive and Inferential Statistics • Descriptive statistics: Methods used to summarise and describe data, such as measures of central tendency and graphs. • Inferential statistics: Methods used to make predictions or generalisations about a population based on sample data. Fill in the blank: Methods used to summarise and describe data are called ______ statistics. Feature Descriptive Statistics Inferential Statistics Primary Goal To summarize and describe the characteristics of a specific dataset. To make predictions or generalizations about a larger population based on a sample. What it tells you "What does our current data look like?" "What does this sample tell us about everyone else?"
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Feature Descriptive Statistics Inferential Statistics Key Tools Mean, Median, Mode, Range, Standard Deviation, Histograms. P-values, Confidence Intervals, Hypothesis Testing (t-tests, ANOVA), Regression Analysis. Nature of Results A factual representation of the observed group. An estimate with a degree of uncertainty (margin of error). Environmental Health Example Calculating the average level of lead found in 500 local water samples last month. Using those 500 samples to predict the likelihood that the entire city's water supply exceeds safety limits. Socioeconomic Example Stating that 15% of a specific surveyed neighborhood lacks high-speed internet. Concluding there is a significant correlation between lack of internet and lower educational outcomes nationwide. Table 1.1 Placeholder: Table comparing descriptive and inferential statistics. Caption: Comparison of descriptive and inferential statistics. Pilot questions 1.1 1. A single numerical value that summarises a characteristic of a sample is called a ______. 2. Statistics helps to identify patterns and trends in ______ occurrence. 3. Methods used to summarise and describe data are called ______ statistics. 4. Give one importance of statistics in environmental health research. 5. What is the difference between descriptive and inferential statistics? 1.2 Types and Classification of Data 1.2.1 Qualitative and Quantitative Data Qualitative data are non-numerical observations that describe qualities or characteristics, for example, gender, occupation, or colour. Quantitative data are
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS numerical observations that can be measured or counted, such as age, weight, or number of hospital visits. Fill in the blank: Non-numerical observations that describe qualities are called ______ data. Figure 1.2 Placeholder: Diagram showing examples of qualitative and quantitative data. Caption: Qualitative and quantitative data. 1.2.2 Primary and Secondary Data Primary data are data collected directly from the source by the researcher, for example, through surveys, interviews, or experiments. Secondary data are data obtained from existing sources such as published reports, hospital records, or government statistics. Fill in the blank: Data collected directly from the source by the researcher are called ______ data. Primary Data (First-Hand) Secondary Data (Existing) Definition: Data collected by the researcher specifically for the current study. Definition: Data collected by someone else previously for a different purpose. Examples: Examples:
LA-NET | ONLINE LEARNING VIDEO PLATFORM FOR POST-SECONDARY & HIGHER INSTITUTION STUDENTS Primary Data (First-Hand) Secondary Data (Existing) * Surveys & Questionnaires: Direct feedback from a community. * Electronic Health Records (EHR): Aggregated hospital visit data. * In-depth Interviews: Qualitative insights into patient barriers. * Government Statistics: Census data or disease registries. * Clinical Trials: Direct measurements from a controlled experiment. * Journal Articles: Systematic reviews of previous studies. * Focus Groups: Group discussions on specific health interventions. * Insurance Claims: Billing data used to track service utilization. Pros: Highly specific and tailored to the research question. Pros: Faster to obtain and often involves massive sample sizes. Cons: Can be expensive and time-consuming to collect. Cons: Researcher has no control over how the data was originally gathered. Box 1.2 Placeholder: Text box listing examples of primary and secondary data. Caption: Primary and secondary data. 1.2.3 Levels of Measurement There are four levels of measurement: • Nominal: Categories without order, e.g., blood group. • Ordinal: Categories with order, e.g., disease severity (mild, moderate, severe). • Interval: Numerical values with equal intervals but no true zero, e.g., temperature in Celsius. • Ratio: Numerical values with equal intervals and a true zero, e.g., weight, height. Fill in the blank: Temperature in Celsius is measured at the ______ level.
This is the opening of the note. Read the full note or download the PDF to continue.
