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Similar to These slides explain the introduction to statistics and biostatistics. Birbhum Pharmacy School (20)
These slides explain the introduction to statistics and biostatistics. Birbhum Pharmacy School
- 1. BIOSTATISITCS AND RESEARCH METHODOLOGY (THEORY) A PPTFor CA-1 of the Introduction: statics, Biostatics. Submitted by: NAME- JOYDIP NANDI COURSE-B. PHARM, 4TH YEAR, SEM-8 SESSION- 2024-2025 REGISTRATION NO. 213530201910004 of 2021-2022 UNIVERSITY ROLL NO. 35301921001 BIRBHUM PHARMACY SCHOOL CAMPUS-BANDHERSOLE, P.O.-HETAMPUR, P.S.-SADAIPUR, DISTRICT– BIRBHUM, PIN-731124, WEST BENGAL
- 2. CONTENTS Introduction Statistics Descriptive Statistics Inferential Statistics Statistical Distributions Biostatistics Fundamentals of Biostatistics Applications in Public Health Study Design and Analysis Data Analysis Data Collection Methods Data Cleaning Techniques Statistical Software Tools Conclusions
- 3. This presentation explores key concepts in statistics and biostatistics, focusing on their importance in research and health sciences. INTRODUCTION
- 5. Descriptive statistics summarize and organize data using measures such as mean, median, mode, and standard deviation. They provide a clear overview of the data and help identify patterns. Visual representations like graphs and charts are commonly used to convey these statistics effectively. DESCRIPTIVE STATISTICS
- 6. Inferential Statistics Inferential statistics allow researchers to draw conclusions about a population based on sample data using techniques like hypothesis testing, confidence intervals, and regression analysis. This branch is essential for making predictions and generalizations beyond the collected data.
- 7. Statistical distributions describe how values are distributed across a dataset. Common types include normal distribution, binomial distribution, and Poisson distribution. Understanding these distributions aids in performing statistical analyses and making inferences about data. STATISTICAL DISTRIBUTIONS
- 9. Fundamentals of Biostatistics Biostatistics applies statistical principles to biological and health-related processes. It encompasses methods for collecting, analyzing, and interpreting data from biological experiments and clinical trials, facilitating advancements in medical research and public health.
- 10. Biostatistics plays a vital role in public health by analyzing data related to health trends, disease outbreaks, and treatment effectiveness. It informs policymakers and health professionals to make data-driven decisions that improve community health outcomes. APPLICATIONS IN PUBLIC HEALTH
- 11. Proper study design is critical in biostatistics. This includes randomization, blinding, and control measures. Biostatisticians analyze the data using appropriate statistical tests to ensure the validity and reliability of study findings, contributing to effective health interventions and policies. STUDY DESIGN AND ANALYSIS
- 12. DATA ANALYSIS 03
- 13. Data collection methods include surveys, experiments, and observational studies, ensuring accurate data gathering. Surveys can be questionnaires or interviews designed to acquire specific information. Experiments allow for control over variables to test hypotheses, while observational studies are crucial for understanding behaviors in natural settings. Selecting the appropriate method depends on the research objectives and the nature of the data required. DATA COLLECTION METHODS
- 14. Data Cleaning Techniques Data cleaning involves correcting or removing inaccurate records from a dataset. Techniques include identifying and handling missing values, correcting inconsistent data entries, and outlier detection. Proper data cleaning ensures high-quality data for analysis, significantly impacting the reliability of results. Automating this process using software tools can enhance efficiency and accuracy.
- 15. Statistical software tools like R, SAS, SPSS, and Python libraries, provide powerful functionalities for data analysis. These tools enable users to perform complex calculations, data visualization, and advanced statistical modeling. Familiarity with these software applications is essential for statisticians and researchers to analyze data efficiently and effectively. STATISTICAL SOFTWARE TOOLS
- 16. In conclusion, understanding statistics and biostatistics is critical for effective research and informed decision-making in the health sciences. By applying proper data collection and analysis methods, adhering to ethical standards, and utilizing biostatistics, researchers can significantly impact public health and policy. CONCLUSIONS
- 17. THANK YOU……