Sample Mean Vs Population Mean

  • date 25th June, 2019 |
  • by Prwatech |
  • 0 Comments

 

Sample Mean Vs Population Mean

 

Sample Mean Vs Population Mean:  Welcome to the world of Data Science tutorials. Are you the one who is looking forward to knowing the differences between the sample mean and population mean which comes under Data Science? Or the one who is very keen to explore what is the sample mean and population mean with examples that are available? Then you’ve landed on the Right path which provides the information about the sample mean vs population mean.

 

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What is Sample Mean and Population Mean?

 

Sample Mean: Sample mean is required in order to predict the outcome from a sample group of items and the whole population by calculating their Arithmetic Mean.

Population Mean: Population Mean is required in order to predict the outcome from the entire data set. It is calculated the Arithmetic Mean of the Whole Population.

Here the accuracy comparatively very high then that of the sample mean.

 

Sample mean and population mean examples

 

Example: Suppose we need to find the voting pattern of National elections in order to predict which party will win.

Here we cannot interview the whole Nations population but we can get some sample data from the population and find its mean.

Hence, we can predict the winner having the highest possibility of winning.

 

Example: Suppose we need to find the average percentage of marks scored by students in a class.

Here we take marks of the whole population of class into consideration to find the class percentage.

 

Sample Mean and Population Mean Formula

 

sample mean and population mean formula

 

How to find Sample Mean and Population mean?

 

Example: how many times a day they eat meals if all 107 candidates in a Gym were surveyed to see.

1 meal (12 people)

2 meals (17 people)

3 meals (38 people)

4 meals (22 people)

5 meals (18 people)

What is the population mean for the number of meals eaten per day?

 

sample mean and population mean example

 

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