# RES710: Week 5 Discussion and Student Reponse

Discussion 1In statistics, it is critical to know what is meant by a normal distribution.

Write a 250- to 300-word response to the following:

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What are the properties of a normal distribution?

Is a normal distribution always necessary? Why or why not?

Why do researchers often refer to a normal distribution as a theoretical normal

distribution?

Include your own experience as well as 2 citations that align with or contradict your comments

as sourced from peer-reviewed academic journals, industry publications, books, and/or other

sources. Cite your sources according to APA guidelines. If you found information that

contradicts your experience, explain why you agree or disagree with the information.

Discussion 2

In Ch. 6, Frankfort-Nachmias and Leon-Guerrero (2018) explore various aspects related to

sampling. Explore the aims of sampling and types of probability sampling. Then refer to your

own mock study topic and variables identified in Week 1.

Write a 250- to 300-word response to the following:

•

•

What types of sampling do you think would be most appropriate for your study? Why?

How does sample size affect the validity of a study?

Include your own experience as well as 2 citations that align with or contradict your comments

as sourced from peer-reviewed academic journals, industry publications, books, and/or other

sources. Cite your sources using APA formatting. If you found information that contradicts your

experience, explain why you agree or disagree with the information.

Student Response 1: Student response 1: Review the classmates’ posts and respond to at

least one in a minimum of 150 words. Explain why you agree or disagree. Then, share an

example from your professional experience to support your assertions.

What are the properties of a normal distribution?

Normal distribution is essential in statistics especially for independent random variables as it

helps to describe the distribution of values for different phenomena. Shaped like a bell, the

normal distribution is a continuous probability distribution that is symmetrical around the

mean, the central peak is surrounded by observation clusters while the probabilities for values

are found farther away from the mean branching off in opposite directions. The normal

distribution looks into how the values of a variable are distributed

The main properties of a normal distribution are the mean, mode and median are equal; half

of the values are to the left of the center and half are to the right; the curve is symmetric at the

center and the total area under the curve is 1.

Is a normal distribution always necessary? Why or why not?

Non normal distributions will usually lack symmetry, or have extreme values, the dome is also

usually shaped differently from a normal bell. While there is nothing wrong with non-normal

data however some traits just do not follow the bell curve. Researchers have to be cognizant of

whether their variables follow normal or non-normal distributions since this ultimately affects

how the data is analyzed. .

Why do researchers often refer to a normal distribution as a theoretical normal

distribution?

Normal distribution is referred to as the theoretical normal distribution because the frequency

distribution is acquired from a formula as opposed to observing actual data. However even

though the normal distribution can be theoretical, the distributions of many fields usually are

similar to normal distribution (IBM, 2022).

References

Frost, J. (2022). Normal Distribution in Statistics. https://statisticsbyjim.com/basics/normaldistribution/

Sainini, K. (2012). Dealing with Non-normal Data. Statistically Speaking, (), 1-5.

IBM. (2022). Normal distribution. https://www.ibm.com/docs/en/cognosanalytics/11.1.0?topic=terms-normal-distribution

Student Response 2: Student response 1: Review the classmates’ posts and respond to at

least one in a minimum of 150 words. Explain why you agree or disagree. Then, share an

example from your professional experience to support your assertions.

What types of sampling do you think would be most appropriate for your study? Why?

In research, it impossible to estimate or study an entire population, therefore the researcher

will conduct a sample which is a representation of the population. Choosing the best sample

means identifying certain factors such as the research objective and the study design. The

different types of sampling are random, stratified, cluster and systematic.

The sampling that will be best for the proposed study is stratified sampling. This type of

sampling method divides the population into subpopulations which might ultimately differ in

some ways. The sampling method helps the researcher to arrive at more precise conclusions by

ensuring that every subgroup is clearly represented. The reason for this choice is to calculate

the individuals from the study who face difficulty in accessing healthcare, this population who

will be sampled in my study from a subgroup this will ensure that the sample clearly identifies

and reflects the population being studied.

How does sample size affect the validity of a study?

When conducting a study, the researcher needs to determine the sample size that will be best

suited for the study. The wrong sample can affect the study, therefore it is important to have

the appropriate sample size. If the sample is too small or too large then the results of the might

prove unethical. An appropriate sample will result in more efficient research. The data that is

acquired from an appropriate sample is usually more reliable and conforms to a more ethical

approach (Faber& Fonseca, 2014).

Reference

Faber, J., & Fonseca, L. M. (2014). How sample size influences research outcomes. Dental press

journal of orthodontics, 19(4), 27–29. https://doi.org/10.1590/2176-9451.19.4.027-029.ebo

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