Basics of Probability and Statistics Week 1 Challenge

1.Type a detailed answer for each of the question that is mentioned above ?
when we use N instead of N-1, we have an error called statistical bias,
which means that the sample variance (the estimator) is systematically different from the true
population parameter (in this case, the variance).

2. Difference between stratified and clustered sampling

In Cluster Sampling, the sampling is done on a population of clusters therefore, cluster/group is considered a sampling unit.
In Stratified Sampling, elements within each stratum are sampled.
In Cluster Sampling, only selected clusters are sampled.
In Stratified Sampling, from each stratum, a random sample is selected.
In Cluster Sampling, the aim is to reduce cost and increase the efficiency of sampling.
In Stratified Sampling, the motive is to increase precision to reduce error.

3. How many different samples can be created out of population of size n

When we are looking to pick n items of a set of n items, we can do so in just 1 way.
For example, if 10 students out of 10 have to be picked,
this can be done in only 1 way because every group picked will have the same 10 students

4. What is the probability of drawing 2 jacks from a pack of card

If there are 52 cards, and 2 of them are Jacks, the probability of drwaing a Jack is 2 out of 52,
because there are 2 Jacks out of the 52 cards you have total.

5. What is the probability that both the numbers on dice are same while rolling 2 dice

1/6

6. Why standard deviation when variance can measure the dispersion in data

the mean is the average of the range of given data values, a variance is used to measure how far the data values
are dispersed from the mean and the standard deviation is
the used to calculate the amount of dispersion of the given data set values.

******Hope everything is correct if any mistakes please mention in remarks and can we also submit ans in text files aslo?? p;ease mention this thank you************