Biostatistics Lecture Notes PDF

# 4th lecture ## Biostatistics Dr. ABASS ALKHALAF Public Health (2024) ## Statistics vs. Biostatistics - **Statistics:** A method of describing, summarizing, or displaying a set of data. - **Biostatistics:** The branch of statistics responsible for the proper interpretation of scientific data gene...

# 4th lecture ## Biostatistics Dr. ABASS ALKHALAF Public Health (2024) ## Statistics vs. Biostatistics - **Statistics:** A method of describing, summarizing, or displaying a set of data. - **Biostatistics:** The branch of statistics responsible for the proper interpretation of scientific data generated in clinical medicine, biology, public health, and other health sciences (e.g., biomedical sciences). - Biostatisticians use mathematics to enhance science and bridge the gap between theory and practice. ## Use of Statistics in Dentistry - **To assess the state of oral health:** - Define and quantify diseases in the community. - Determine the availability of and utilization of dental care facilities. - **To indicate the basic factors and causation of oral diseases:** - Diagnose the community. - Identify solutions to problems. - **To plan oral health measures.** - **To determine the success or failure of specific oral health care program or measures:** - Evaluate programs. - Conduct comparisons and researches. ## Data Data are any information that can be collected, such as age, gender, height, and weight. ## Variables - **Variable:** An attribute that describes a person, place, thing, or phenomenon which can take different values. - **Types of Variables:** - **Independent Variable:** Influences the dependent variable. - **Dependent Variable:** Changes depending on the independent variable. - **Control:** A variable that remains constant to help isolate the independent variable's effect. - **Types of data:** - **Qualitative:** Information about qualities that cannot be measured. - Classified as: - **Nominal:** No natural order between categories. - **Ordinal:** Ordering exists between categories. - **Quantitative:** Information about quantities. - Classified as: - **Discrete:** Defined in intervals or whole numbers. - **Continuous:** Can take any value. ## Methods of Data Collection - **Census:** A study that obtains data from every member of a population. - **Sample Survey:** A study that obtains data from a subset (sample) of a population to estimate population attributes. - **Experimental Study:** A controlled study where the researcher attempts to understand cause-and-effect relationships. The researcher controls how subjects are assigned to groups and what treatments each group receives. - **Observational Study:** Similar to experimental studies in wanting to determine cause-and-effect relationships. However, the researcher cannot control how subjects are assigned to groups or which treatments they receive. ## Sampling Technique - It is difficult to study all members of a population due to constraints of time and money. - Sampling errors can occur due to faulty sampling design (e.g., sample size), as well as non-sampling errors such as coverage error, observational error, or processing error. ## Sample Selection - **Purposive Selection:** The researcher specifically chooses people for a study or research project. The goal is to concentrate on people with particular characteristics who will be able to assist with the research. - **Random Selection:** A sample of units is selected in a way that all the characteristics of the population are reflected in the sample. Each unit in the population has an equal chance of being in the sample. ## Random Sampling Designs - There are various sampling designs depending on the type and nature of the population and the objectives of the investigation. - **Simple Random Sampling:** Each element has an equal chance of being included in the sample. - **Systematic Random Sampling:** Select one unit at random, then select additional units at evenly spaced intervals. - **Stratified Random Sampling:** The population is subdivided into groups (strata) based on a specific characteristic. A simple random sample is selected from each strata. - **Cluster Sampling:** The population is broken down into clusters, and a sample of clusters is selected. All elements in the selected clusters are surveyed. - **Multiphase Sampling:** Collect information from the whole sample and then from a subset of the sample. ## Sample Size - A larger sample size can yield more accurate results. - The sample size should be defined before starting a clinical study so as to avoid bias. - If the sample size is too small, the results cannot be generalized to the population. ## Data Presentation - The collection of numerical information often leads to large masses of data that need to be summarised and analyzed. - **Tabulation of Data:** Data is presented in a table. (Frequency Distribution Tables) - **Graphical Representation of Data:** Visual display of data using plots and diagrams. - **Histogram:** Used to show the frequency distribution of quantitative data. No gaps between bars. Taller bars indicate higher frequencies. - **Bar Graph:** Used to show qualitative data. Bars can be plotted horizontally or vertically. - **Simple Bar Graph:** It represents a single variable. - **Multiple Bar Graph:** Used for data with two or more components. - **Sub-divided Bar Graph (Component Bar):** Bars are divided into parts representing different components for data with many categories and subcategories. - **Frequency Polygon:** A line graph connecting the mid-points of the histogram blocks. - **Pie Diagram:** Used to show the contribution of each item to the whole. - **Line Graphs:** Connect data points with line segments to show changes over time. - **Scatter Plots:** Visualize the relationship between two variables. - **Statistical Maps:** For geographic or regional distribution of data. - **Pictogram:** Uses small pictures or symbols to represent data.