Basics of Probability and Statistics Week 1 Challenge

1.Why there is a difference in the formula of variance for population and sample.

* N is a greater value than N-1.
* When divided N-1 a smaller number we will get a larger number for variance. This number near to the possible variance value
for the population.
* It is always good to have a large variance for the population. This helps in further analysising data with out any bias.

2.Difference between stratified and clustered sampling.

Stratified sampling:
* This is a sampling method where population are divided into homogenous segment and then the sample is randomly taken from
the segment.
* Randomly selected individuals are taken from all the strata.
* Imposed by researchers. This type sampling increases precision and representation.

Cluster sampling:
* This is a sampling method where the entire cluster us selected randomly. Clusters are naturally occuring group.
* All the individuals are taken from randomly selected cluster.
* Naturally occuring groups. To reduce cost and effeciency.

3.How many different samples can be created out of population of size n
Npn = N!/(N-n)!
n = sample size

4.What is the probability of drawing 2 jacks from a pack of card.
No of cards in a deck = 52
No of jack in a deck = 4

Probalility of drawing 2 jacks from a pack of card = 1/26.

5.What is the probability that both the numbers on dice are same while rolling 2 dice.
Probability of getting 2 same number = 1/6.

6.Why standard deviation when variance can measure the dispersion in data.
Variance calulated will produce a value with unit of measurement is not similar to data.
Standard deviation calculated after squaring the variance will produce unit of measurement as the data.