Lecture´s Description

*The predominant concept which has been elaborated in this sqadia.com medical V learning lecture is the probability and distributions. This lecture provides a detailed comprehension of independence, probability along with the binomial and poison distribution. Moreover, continuous and normal distribution
in conjunction with the central limit theorem and conditional probability has been brought under discussion. *

**Independence**

In this lecture **´´****Probability and Distributions****´´ **are explained. Section one is about **´´Independence´´.** Initially, educator gives information about **independence: data and variables.** Then explains **independent and dependent variables** through **graphs** and **examples**. After that elaborates **independence: data and variables** and clears the concepts using different **examples**. In the end, **independence matters** are discussed.

**Probability**

Section two is about **‘’Probability’’**. At first educator gives an overview of **probability**. After that **rules of probability** are discussed. Then **interpretation of properties of probability** is given. This is followed by **examples of probability using coin tossing**. Moreover, **probability distributions**
come under consideration along with **one coin example **and** two coin example**. At last **example for probability distributions** is pursued.

**Binomial and Poisson Distribution**

Section three is about **‘’Binomial and Poisson Distribution’’**. Educator begins by explaining **binomial distribution: formula. **Then illustrates binomial distribution graphically. Following this, talks about **Poisson distribution**. After that **Poisson distribution with different means** is elaborated. Likewise, **exemption from Poisson distribution** is focused. At last, information about **Poisson distribution: mean and variance **is conveyed.

**Continuous and Normal Distribution**

Section four is about **‘’Continuous and Normal Distribution’’.** Educator's first theme of discussion here is **continuous probability distributions**. After that information is delivered about **interpreting continuous probability distribution**. Then **normal distribution** is elucidated. Moreover, educator sheds lights on **converting to standard normal distribution**. Later on, **normal distribution: calculating probabilities** is thoroughly discussed. Lastly, **normal distribution: percentage points**
is highlighted.

**Central Limit Theorem and Conditional Probability**

Section five is about **‘’Central Limit Theorem and Conditional Probability’’. **Educator primarily focus on **central limit theorem**. Then tells the **advantages of using normal distribution**. Likewise, **consequences of central limit theorem** are elaborated encompassing **binomial distribution **and** ****Poisson distribution**. Next subject of elucidation is **conditional probability**. In the end of this section, **Bayes’ theorem** is pursued.