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B Pharm Biostatistics and Research Methodology Unit 2 PDF Notes

Updated: Feb 9


B-Pharmers, dive deeper into the data analysis game with B Pharm Biostatistics and Research Methodology Unit 2 PDF Notes! Buckle up as we explore regression, where you'll learn to fit lines and curves to data, predicting trends and relationships like a pro. Imagine figuring out how drug dosage affects blood pressure or how two medications interact. We'll tackle different equations, from simple linear models to powerful multiple regression. But statistics isn't just about lines; it's about understanding chance and uncertainty. We'll introduce you to probability, the language of chance events, and delve into distributions like binomial and normal curves, predicting how likely certain outcomes are. Feeling scientific? We'll explore hypothesis testing, where you'll learn to make informed decisions based on data, considering factors like sample size and errors. Parametric tests like t-tests and ANOVA come into play, helping you compare groups and draw meaningful conclusions. By the end of this unit, you'll be a statistics master, equipped to analyze complex healthcare data and make data-driven decisions that improve patient care and advance scientific discovery!


B Pharm Biostatistics and Research Methodology Notes
B Pharm Biostatistics and Research Methodology Notes

B Pharm Biostatistics and Research Methodology Unit 2 PDF Notes


Unit 2


Regression: Curve fitting by the method of least squares, fitting the lines y= a + bx and x = a + by, Multiple regression, standard error of regression– Pharmaceutical Examples

Probability:Definition of probability, Binomial distribution, Normal distribution, Poisson’s distribution, properties - problems Sample, Population, large sample, small sample, Null hypothesis, alternative hypothesis, sampling, essence of sampling, types of sampling, Error-I type, Error-II type, Standard error of mean (SEM) - Pharmaceutical examples


Parametric test: t-test(Sample, Pooled or Unpaired and Paired) , ANOVA, (One way and Two way), Least Significance difference


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