In your opinion can you explain the difference between a population and sample and why do we normally study a sample than a population?

Provide a brief discussion of the following. Include examples in you response to enhance my understanding: systematic sample; stratified sample; weighted mean; standard deviation; mutually exclusive events; independent events; and expected value

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Statistics
In your opinion can you explain the difference between a population and sample and why do we normally study a sample than a population?

Provide a brief discussion of the following. Include examples in you response to enhance my understanding: systematic sample; stratified sample; weighted mean; standard deviation; mutually exclusive events; independent events; and expected value
Solution:
Samples and populations:

Statisticians carry on endlessly about two particular terms - 'population' and
'sample'. There is in fact good reason for the emphasis placed on these concepts
and we need to be clear about the distinction.

Population

One of the hall-marks of good research is that there should be a clear definition of the
target group of individuals (or objects) about whom we are aiming to draw a
conclusion. The term 'population' is used to cover all the individuals who fall within that target group. The experimenter can define the target group as widely or narrowly
as they see fit. Some experiments may be very general, with the intention that our
conclusions should be applicable to the entire human race or all the cats or all the dogs
on the planet. In other cases, the target may be much more narrowly defined; perhaps
all the females aged 55-65 with moderate to severe rheumatoid-arthritis, living in
North America. The size of the population will vary accordingly. At one extreme (all
humans) there might be 6000 million of them, whereas the group with arthritis
(defined above) might contain only a few million.

Population
The complete collection of individual's about whom we wish to draw some conclusion.

While the sizes of populations may vary, they all tend to be too large for us to be able
to study them in their entirety. Of course, it is possible to define a population so
tightly that the numbers become ...

Can you tell me why are samples studied when we want to know about populations? Why are random samples used instead of just any sample? How would you determine an appropriate sample size? If there are any reference please provide.

Greek letters are used to describe characteristics of
A) samples and populations.
B) samples and sampling distributions.
C) sampling distributions and populations.
D) samples, sampling distributions, and populations.

Please help with the following problems involving normal distribution and populations.
Based off the three requirements that must be met before an analysis of variance test (ANOVA) can be used:
1. Samples must be randomly selected from the populations to be evaluated.
2. All populations from which the samples are selected

SS within samples is a sum of squares representing the variation that is assumed to be common to all the populations being considered. Is this true? Explain

1.Why would you use a small sample to draw inference about a large population?
Test of a single proportion:
2. What is the difference between a sample parameter (X-bar and s) and a proportion parameter (p)?
Test of two populations, large sample size (z-statistics)
3. When would you use two population test with a larg

1. Give a scenario that would require you to use a non-parametric statistic, such as ranking.
2. Also choose any statistician and find an interesting fact about them.
Please provide an answer of good quality, length and merit.

The following ANOVA table based on information obtained for 3 samples from 3 independent populations that are normally distributed with equal variances has a few missing values.
a) Find the missing values and complete the ANOVA table.
b) Using α = .01, what is your conclusion for the test with the null hypothesis that

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Test the claim below about the mean of the difference of two populations. Use a t-test for dependant, random samples at the given level of significance with the given statistics. Is the test right-tailed, left-tailed, or two-trailed? Assume the populations are normally distributed.
Is the test right-tailed, left-taile

Need help with one psychological research question that could be answered by each of the following types of statistical tests:
a) Z test and T test for independent samples
b) T test for dependent samples
c) Rationale for both selections so I might be able to understand better

If we are testing for the difference between the means of 2 related populations with samples of n1 = 20 and n2 = 20, the number of degrees of freedom is equal to
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Show all work.