Statistics Part-1

Index :

?Statistics

-> Definition

-> What Exactly is Data?

?Types of Statistics

-> 1.What Is Descriptive Stats?

-> 2.Inferential Stats

?Problem Statement Framing

?Sampling Techniques

-> 1.Simple Random Sampling

-> 2.Stratified Sampling

-> 3.Systematic Sampling

-> 4.Convience Sampling

?Statistics

Definition :

Statistics is the science of Collecting, Organizing and Analysing data.

What Exactly is Data?

Facts or pieces of Information.

• Eg 1 : Age of Students in a classrooms {24, 30, 21 , 34 , 20}
• Eg 2 : Weights of Students in a classroom { 75,45,50, 55,60}

Can I find some information about the data?

Like can we calculate the Mean ,Median of the data we can put them in the term of Analysis.

?Types of Statistics

????

There are two types of Statistics

1. Descriptive Stats
2. Inferential Stats

1. What is Descriptive Stats?

It Consists of Organising and Summarising of data.

E.g : Histogram , Bar Chart , pdf (Probability distribution function) , Pie Chart , Box Plot(Horizontal) , Candle Stick(Vertical)

2. Inferential Stats

It Consists of a Technique to form some conclusions.

• Example : Suppose a researcher wants to understand the average height of adult men in a city. It’s impractical to measure every adult male in the city, so the researcher decides to take a random sample.
• Process Collect data Calculate sample statistics Make inferences Use hypothesis testing → We'll come up with some kind of conclusion for the sample data
• What all technique we specifically use are Eg. p value , Z test , t-test , chi square test , Annova test

Interview Question asked in the Amazon

What is the average size of All Sharks in the World?

Answer me in comment which type of Statistics we'll use is it gonna be descriptive or inferential?

? Problem Statement

E.g ) Lets say there are 20 classrooms in a university and you have covered the age of students in one classroom -

Ages {21 ,20 , 18 , 34, 17 , 22 , 24, 25 , 26 , 23 ,22 }

???? Descriptive Questions

How's the question can be there in descriptive?

How's the question can be there in descriptive?

Descriptive Stats : What is the average age of the Students in the classroom??

Other possible questions

• or Which is the Minimum age or
• What is the Outliers,
• What kind of the distribution my data follows ,
• Can be do any kind of transformation for the particular data?
• What is the maximum age?

???? Inferential Questions

• Are the average ages of the student in the classroom equal to the average ages of the entire university here we can say : student in the classroom is sample data Average ages of the the entire university - Population data conclusion - Average age
• Population is denoted by ‘N’
• Sample is denoted by ‘n’

For simplicity:

Inferential statistics is about using a small group (sample) to learn about a larger group (population).

We collect data from the sample, analyze it, and then make conclusions or predictions about the population.

? Sampling Techniques

1. Simple Random Sampling

• Every Member of the population (N) has an equal chance of being selected for your sample (n)
• E.g : When tossing a coin what is a probability of getting a head is 1/2 and probability of getting tail 1/2 i.e equal chances

2. Stratified Sampling

• By splitting a population into smaller groups, or strata, that have comparable traits, stratified sampling is a sampling technique.
• After that, a random sample is drawn from each stratum to guarantee that every subgroup is fairly represented in the sample as a whole.
• This method improves in increasing the sample's representativeness and accuracy.

Ex :

• Assume a corporation wishes to measure employee happiness across departments.
• The organization is divided into five departments: marketing, sales, human resources, information technology, and finance.
• To ensure that each department's perspectives are reflected, the corporation splits its personnel into five strata and selects an equal number of people from each.
• This approach ensures that the sample reflects the overall variety of the organization.

3. Systematic Sampling

• Systematic sampling is a probability sampling method where you select a sample from a population by choosing a starting point randomly and then selecting every Kth element.
• The interval is calculated by dividing the population size N by the desired sample size n (K = N/n).

Example :

Example: For a population of 1000 and a sample size of 100, set k = 10 . Starting from a random point (e.g., 4), select every 10th person (4, 14, 24, etc.) to get a well-spread sample.

4. Convenience sampling

• Only those people who are interested will only be participated
• Convenience sampling is a non-probability sampling method in which samples are collected from a population group that is easily accessible or reachable.
• It is based on gathering data from people who are easily accessible, which frequently leads to faster and more cost-effective solutions, but it may introduce bias because it does not reflect the full population.

Example :::

Surveying pupils in your class since they are close by and easily available, rather than sampling from the entire school.