FerrellJEDR8201-1a

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Northcentral University *

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8201

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Statistics

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Jan 9, 2024

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FerrellJEDR8201-1a 1 Examine the Basic Principles and Concepts Joyce E. Ferrell Department of Education, Northcentral University EDR-8201: Statistics I Dr. McKenna November 5, 2023

FerrellJEDR8201-1a 2 Week 1: Basic Principles and Concepts 1. Population and sample: a. What is a population? Give an example of a population. A population is the complete group that desires to be tested or questioned. According to Chadwick (2017), a population can be narrow or broad in span. It is nearly impossible to test an entire population. If I wanted to test the effects of cellphone usage on academic skills, an example of a population is “American students under the age of 18.” b. What is a sample? Give an example of a sample from the population given in 1a. A sample is a part of the population that can be tested. It includes a manageable size of the population to produce acceptable representative data. An example of a sample from the population given in 1a would be “American students between the ages of 13-18 that utilize cellphones for schoolwork. 2. What is the difference between a sample and a parameter? Explain using examples. A sample is a part of the population that can be tested. A parameter is the number value that describes the entire population. An example parameter from the example I provided is the “mean age of students under the age of 18 in America or the average hours a day that students under the age of 18 utilize cellphones.” 3. What is the margin of error in statistics, and why is it important? A percentage of error results from the data that can stray from prior to affecting the credibility of the study is the margin of error. The greater the error is, the less reliable the results are. It is important because it conveys the reliability and limitations of survey results, essential for informed decision-making and accurate interpretation of data.

FerrellJEDR8201-1a 3 4. What is the difference between quantitative and qualitative data? Quantitative data can be counted in numbers and measurable. Qualitative data is not measurable by numbers and is used to describe qualities or characteristics. Quantitative data gives information on how many and how much. Qualitative data gives information about why, how, or what happens as a result of certain behaviors. 5. Describe the four scales of measurement a. Nominal- data can be category labels but non-ranked information. b. Ordinal- data can be ordered, categorized, and ranked. c. Interval- data can be categorized and ranked with equal spacing between data points. d. Ratio- data has an absolute zero. 6. Provide examples of variables found in educational research that fall under each of the four scales of measurement described above. a. Nominal- Qualitative data: gender, race, marital status b. Ordinal- Qualitative data: satisfaction level, rankings of school students, letter grades c. Interval- Quantitative data: temperature, SAT score d. Ratio- Quantitative data: weight, height 7. What is a hypothesis? A hypothesis is an educated guess used to make predictions. The words “if” and “then” are statements used to represent the sample and population. 8. What is a hypothesis test?

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