# EDR 8201 ASU Standard error and Parametric Assumptions Paper

Six days ago, this question was completed by you. However, I recieved a grade of F because all questions/sections was not completed. I am resubmitting this question for your completion. Below, is an attachment of the incomplete answer to the question. Thanks in advanced.

## Instructions

## Part I. Inferential Statistics Concepts and Assumptions & Concepts

What is the standard error of measurement?

What is the standard error of the mean?

Calculate the standard error of the mean (SEM)? (Note: SEM is calculated by dividing the standard deviation by the square root of the sample size.)

Why is it better to use a 99% CI then a 95% CI?

Explain a 95% CI and give an example or apply the meaning in a real-world situation (you do not need to calculate by hand but can if you want to! OR you could create a fake dataset on SPSS and have SPSS calculate the CI, OR make it up OR use an online CI calculator such as

https://www.mathsisfun.com/data/confidence-interval-calculator.html

). The point of this assignment question is for you to understand what the 95% CI means.

A *movie* company wants to test if there are movies that are preferred more by females and preferred more by males. The movie company surveyed 20 men and 20 women and showed half of each sample a film that was supposed to be a movie preferred more by females (The Notebook) and males (The Godfather). In all cases, the movie company measured their excitement as an indicator of how much they enjoyed the film. Please open the movie SPSS file, and answer the following questions:

Conduct the required analyses to test for the assumptions of normality (Shapiro-Wilks or Kolmogorov-Smirnov) and homogeneity of the variance (Levene’s) for the two films from the data in the movie data file.

Remember that there are additional Supplemental Resources available for each week in the Course Resources linked at the top of your course.

Length: Complete responses to all questions in all three parts. Please include the question prompts along with your responses in your assignment submission. In addition to a WORD (.doc) file with the answers to the assignment questions, also include the output (.spv) file. (*NOTE*: SPSS automatically generates the .spv file as you work in SPSS. When you close your SPSS main window, SPSS will ask you if you want to save the output file. Click ‘yes’, then save to your computer and upload with your assignment.)

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Assignment: Standard error and Parametric Assumptions

Peniel Dany

Northcentral University

EDR-8201 Statistics

Dr. Rodriguez

March 21, 2022

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Standard error and Parametric Assumptions

Part I: Inferential Statistics Concepts and Assumptions

In performing statistical analysis, standards error of measurement (SEM) is an imperative

concept in inferential analysis. SEM estimates the distribution of a repeated measure from an

instrument around the score. Pyrczak and Oh (2018) noted that SEm is meaningful in test-taking

because it applies to a single score using the same units as the test, estimating the variation

around the correct score of individual repeated measures. Thus, SEm facilitates the ability to

examine the reliability of the scores in a trial, describing the extent of the consistency of test

results on different occasions. On the other hand, the standard error of the mean establishes the

variability of data points from the average, evaluating the precision of a sample mean, also

referred to as the standard deviation of the sample mean of the distribution taken from a

population

The confidence interval describes the probability that a parameter would fall between two

values around the mean, measuring the degree of uncertainty or the certainty in sampling

techniques. In an excellent example, a researcher may use a confidence interval such as 95 % or

99% to define the interval within which the estimated population means would fall.

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References

Pyrczak, F., & Oh, D. M. (2018). Making sense of statistics: A conceptual overview. Routledge.