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Write a 700- to 1,050-word scholarly paper that explains the following:

- The difference in population and sample
- Types of sampling techniques
- Using your proposed dissertation, the type of sampling that would be most appropriate
- How will you access this sample

Then part two in a separate document:

Using

G*Power

and the information provided, answer the following:Problem 1:

To what extent does age, race, and gender predict the annual salary of bank presidents?

Conduct an

*a-priori*

analysis, a medium effect size, and alpha of .05 and a power of .80.What is the sample size you need to prevent a type II error?What is a type error, and how does an adequate sample prevent it? Show your work by providing your G*Power output.Problem 2:

What is the difference in growth rate between publicly traded enterprises and privately held firms?

Using a post hoc analysis with a sample size of 100, a medium effect size, and an alpha of .01, what is the power of your study?Explain what the power value means.Show your work by providing your G*Power output.

Problem 3:

What is the difference in self-efficacy, burnout, and workload among hospital, university, and manufacturing administrators?

Conduct an

*a-priori*

analysis using a large effect size, an alpha of .05, and a power of .95. What is the total number of participants needed in your sample?How many participants do you need in each group?Why is it important to have an equal number of participants in each group?Show your work by providing your G*Power output.Write your answers in a single document.

Answered 2 days AfterApr 30, 2021

A population is basically the collection of the people and items or the events that can be making the inferences. It cannot have the convenient or the

A sample can be the subset of the people, items and events that can be having the larger population that can collect for the analysing or making the inferences. TO represent the population to the well and the sample should be randomly to collect and the adequately large.

Population vs Sample

The major difference between the population and the sample with we can do the observation that are assigned to the data set.

A population can be including the element from the data set.

A sample can be consisting to the one or more observation drawn from the population. More than the sample that can be derived from the sample of the same population. The other differences can be notation and the computations.

For example: A measurable that can have the characteristics of the population like the mean or the standard deviation and it is called the parameter but the measurable characteristics of the sample and it is called the statistics.

2) Types of sampling techniques

The two types of sampling techniques and these are following:

Probability Sampling

Non- Probability Sampling

Probability Sampling

The sampling technique can be used for every element of the population and it can get the equal chance of the sample which can be selected. It is also called the random sampling.

Simple Random Sampling:

Every element has the equal amount of the chance that can get the selected for the par to the sample and it can basically use for the prior information to the target population.

Stratified Sampling

The stratified sampling is the technique that can be divided for the elements of the population into the small subgroups and that is basically based on the similarity in...

SOLUTION.PDF## Answer To This Question Is Available To Download

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