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Biostatistics using SPSS

  • 4.7(45,582 Rating)

Course Overview

7 high-quality and relevant video-based Courses with 14+ hours of well-designed, well-crafted study materials on SPSS, Descriptive Statistics, Correlation Techniques, Scatter Plot, Linear Regression, T-Value, Regression Equation, MS Excel, Multiple Regression Modeling, Logistic Regression, Multinomial Regression, Statistical Analysis, Basic Data Management, Correlation Analysis. Learn by doing. Verifiable Certificate of Completion for Courses. Full Lifetime Access. Begin your path toward becoming a professional data consultant for several research studies. Learn how to gather, organize, and statistically analyze research data. Refines your role as a Statistical Data Analysis Manager or higher-level researcher in the corporate world. The focus of the current training program will be to help participants learn statistical skills through exploring SPSS and its different options. The focus will be to develop practical skills in analyzing data and developing an independent capacity to accurately decide what statistical tests will be appropriate for a particular kind of research objective.

Eligibility / Requirements

Prior knowledge of Quantitative Methods, MS Office and Paint is desired.

Target Audiance

  • The meticulous analyst, scrutinizing every data point for insights.
  • The eager novice, absorbing every SPSS function with enthusiasm.
  • The skeptical traditionalist, reluctantly embracing statistical software.
  • The methodical researcher, applying biostatistics principles with precision.
  • The collaborative learner, seeking group discussions to grasp complex concepts.

Schedule Dates

Biostatistics using SPSS
02 December 2024 - 06 December 2024
Biostatistics using SPSS
02 March 2025 - 06 March 2025
Biostatistics using SPSS
02 June 2025 - 06 June 2025
Biostatistics using SPSS
08 September 2025 - 12 September 2025

Course Content

  • Quantitative & qualitative analysis
  • Sample size with Minitab, Pass and excel
  • Sampling with Excel
  • Descriptive analysis
  • Multiple responses
  • Parametric methods and hypotheses tests
  • Dealing with missing data
  • Exercises

  • Correlation analysis
  • Simple Linear Regression
  • Simple and Multiple Linear Regression
  • Detecting & addressing outliers
  • Regression assumptions and diagnoses
  • Linearity assumption
  • Normality assumption
  • Homoscedasticity assumption
  • No autocorrelation assumption
  • Exercises

  • kolmogorov smirnov test
  • Test of one sample
  • Test of two independent samples
  • Test of K-independent samples
  • Test of median equality
  • Exercises

  • Two Way ANOVA
  • Factor Analysis
  • Quantile regression
  • Non-linear regression
  • General linear model
  • Generalized linear model
  • Exercises

  • Odds ratio, Relative risk
  • Logistic Regression
  • Multinomial Regression
  • Ordinal Regression
  • Life Tables
  • Survival Analysis using Kaplan Meier
  • Cox Regression
  • Roc Curve
  • Longitudinal data analysis
  • Exercises
  • Review course objectives and suggestions

FAQs

Biostatistics is the application of statistical methods to biological and medical data. It plays a crucial role in healthcare research by helping analyze and interpret data from clinical trials, epidemiological studies, and other research endeavors, leading to evidence-based decisions in healthcare.

SPSS (Statistical Package for the Social Sciences) is a software package used for statistical analysis. It’s popular in Biostatistics due to its user-friendly interface, extensive statistical capabilities, and compatibility with healthcare research data formats.

While prior statistical knowledge is beneficial, this course is designed to cater to beginners as well as those with some familiarity with statistics. We’ll cover basic statistical concepts before delving into more advanced topics.

You’ll learn to analyze various types of healthcare data, including clinical trial data, patient demographics, disease prevalence, treatment outcomes, and epidemiological data.

Yes, the course will cover both descriptive statistics (summarizing and visualizing data) and inferential statistics (making predictions and testing hypotheses) using SPSS.

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