# 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.

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

What is the standard error of measurement?

What is the standard error of the mean?

• Please discuss the term confidence interval.
• What are four main assumptions for parametric statistics?
• Please discuss and explain in your own words each of the four main assumptions.
• Why it is important to discuss or test the assumptions before conducting parametric statistical analyses?
• Part II. Standard Error of the Mean and Confidence Intervals
• A district-wide test is used to measure math aptitude in freshmen in high school students, with a mean of 78 and a standard deviation of 12. Thirty-six selected freshmen took the test, and their mean score was 85. You are tasked to examine if these students are significantly different from the district test group.
• 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.

• Explain a 99% 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 99% CI means.
• Part III. Testing for Parametric Assumptions
• 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.

• Please write a few sentences describing the assumptions required in this exercise and whether or not they were met. Please include information from the output to support your answers.
• 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.

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