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Coursework, Education, Pages: 1

Week 1 Part 1 Assignment

Week 1 Part 1 Assignment

Question 1

A population is the entire group of individuals, objects, or events that the researcher may or may not be interested in studying, recording, or measuring (Chadwick, 2017). For instance, if a researcher wanted to learn how college students read in the US. In this case, all college students in the US would be the population: Week 1 Part 1 Assignment.

Conversely, a sample is a subset of people who are selected for study. A sample in the case above could be a group of 250 students chosen in a random manner from universities spread all over various states.

Question 2

A parameter represents a trait of the whole population, and a sample statistic is an observable trait of a sample (Chadwick, 2017). For example, one may need to know the sample mean of all adult males in the United States, the US population, and this is the parameter. Still, if one measures the height of a sample of 1,000 adult males, one would get a sample statistic called the average height of this group.

Question 3

The margin of error is the measure of the random part of a survey’s result. This is important because it tells one how much faith they can place that the sample results are or are not working for the population.

Question 4

Quantitative data is a data that can be counted, measured, and expressed by numbers, and it is different than qualitative data because it is data of qualities or characteristics (Coleman, 2018b). For example, if a researcher asks participants their age, their data would be quantitative. Nevertheless, if the researcher engages with participants to describe their experiences with a product, these responses are qualitative data.

Question 5

There are four scales of measurement. These are nominal, ordinal, interval and ratio (Coleman, 2018b). Categorical data without any order or hierarchy is called nominal data, such as gender or race. Ordinal data has an order or hierarchy, but the distances between each value are not the same, for example, grades awarded in letters (A, D, B, …).

To provide an example, temperatures consisting of Celsius or Fahrenheit are not interval values; these are ordered data with certain intervals between values but without a true zero point. However, there is an order, true zero points, equal intervals, and ratio data for height and weight.

Question 6

In educational research, examples of variables that fall under each scale of measurement could be:

  1. Nominal: gender, race, or academic major
  2. Ordinal: letter grades or class rank
  3. Interval: standardized test scores or IQ scores
  4. Ratio: number of years of education or teaching experience

Question 7

A hypothesis is a proposed explanation for a phenomenon that is testable by research.

Question 8

A hypothesis test is a statistical method in which the evidence of a sample of data is found enough to believe that a given condition that is held in that population is also held in the entire population.

Question 9

The null hypothesis (H0) is the same as the statement that there is no significant difference or relationship between variables. For instance, a null hypothesis would state, “Blood pressure is the same in patients taking the new drug as in those on the standard treatment.”

Alternative hypotheses (H1) state that there is a large difference or relationship between variables (Coleman, 2018a). Accordingly, an example is, “The new drug was more effective at lowering blood pressure compared to the standard treatment.”

Question 10

According to Coleman (2018a), the p-value is the probability of getting the observed results (or more extreme) if the null hypothesis is, in fact, true. Typically, researchers aim for a p-value below 0.05. If the p-value falls under this value, they reject the null hypothesis and accept the alternative hypothesis.

References

Chadwick, A. (2017). Population/sample. In The SAGE Encyclopedia of Communication Research Methods. SAGE. https://dx.doi.org/10.4135/9781483381411

Coleman, J. S. (2018a). Hypothesis testing. In B. B. Frey (Ed.), The SAGE Encyclopedia of Educational Research, Measurement, And Evaluation (pp. 803-969). SAGE.

Coleman, J. S. (2018b). Levels of measurement. In B. B. Frey (Ed.), The SAGE Encyclopedia of Educational Research, Measurement, And Evaluation (p. 969). SAGE.

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Question

Week 1 instructions

Please answer each of the following questions using information from the readings. Ensure you understand each term and explain in your own words. Also, give your own real-world example of each concept to ensure understanding of the concept.

  1. Population and sample:
    1. What is a population? Give an example of a population.
    2. What is a sample? Give an example of a sample from the population given in 1a.
  2. What is the difference between a sample and a parameter? Explain using examples.
  3. What is the margin of error in statistics, and why is it important?
  4. What is the difference between quantitative and qualitative data? Do not just paste definitions of each-fully explain in your own words the difference between these two methodologies.
  5. Describe the four scales of measurement
    1. Nominal
    2. Ordinal
    3. Interval
    4. Ratio
  6. Provide examples of variables found in educational research that fall under each of the four scales of measurement described above.
    1. Nominal
    2. Ordinal
    3. Interval
    4. Ratio
  7. What is a hypothesis?
  8. What is a hypothesis test?
  9. Statistical hypothesis:
    1. What is the null hypothesis? Write an example of a null hypothesis.
    2. What is the alternative hypothesis? Write an example of an alternative hypothesis.
  10. Please explain what a p-value is for a hypothesis test. What alpha level do researchers generally use to test significance of the p-value?

Length: 1 page

References:

  • Population/Sample
    Chadwick, A. (2017). Population/sample. In The SAGE encyclopedia of communication research methods. SAGE. https://dx.doi.org/10.4135/9781483381411

    Note 4/10/24: If the Link URL does not work try to open this book link https://methods.sagepub.com/reference/the-sage-encyclopedia-of-communication-research-methods
    Look for the Institution login on the top right. Click on that and search for National University.
  • Hypothesis Testing
    Coleman, J. S. (2018). Hypothesis testing. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 803-804). SAGE.
  • Levels of Measurement
    Coleman, J. S. (2018). Levels of measurement. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 969). SAGE.
  • SPSS
    Gordon, M., & Courtney, R. (2018). SPSS. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1577-1583). SAGE.
  • Tutorial
    IBM SPSS. (2022). Tutorial. IBM.
  • Ordinal-level of Measurement
    Ingram, P. B., & Ternes, M. S. (2018). Ordinal-level of measurement. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1185). SAGE.
  • Sampling and Bias
    integral CALC (Producer). (2018). Sampling and bias [Video file]. Films on Demand.
  • Integral CALC
    Integral CALC Statistics Tutorials.

    Week 1 Part 1 Assignment

    Week 1 Part 1 Assignment


    Kulas, J. T., Roji, R., & Smith, A. M. (2021). IBM SPSS essentials (2nd ed.). Wiley.

  • Entering data in IBM SPSS
    Meyers, L. S., Gamst, G. C., & Guarino, A. J. (2013). Entering data in IBM SPSS. In Performing data analysis using IBM SPSS (pp. 5-13). Wiley & Sons.
  • Nominal-level Measurement
    Prion, S. (2018). Nominal-level measurement. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1149). SAGE. http://dx.doi.org.proxy1.ncu.edu/10.4135/9781506326139.n472
  • Scientific Method
    Staddon, J. E. (2018). Scientific method. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 1473-1477). SAGE.
  • Interval-level of Measurement
    Sudweeks, R. R. (2018). Interval-level of measurement. In B. B. Frey (Ed.), The SAGE encyclopedia of educational research, measurement, and evaluation (pp. 871). SAGE.
  • Tutorial for Beginners
    IBM SPSS. (2022). Tutorial for beginners. IBM.
  • Sampling and Bias
    integral CALC (Producer). (2018). Sampling and bias [Video file]. Films on Demand.
  • Stats I Week 1
    Lloyd, C. (2021, July 25). Stats I Week 1 [Video]. Kaltura
  • Encyclopedia of Research Design
    Mitra, A. (Ed.) (2022). Encyclopedia of research design. SAGE. https://doi.org/10.4135/9781071812082
    Note 4/10/24: If the Link URL does not work try to open this book link https://sk.sagepub.com/reference/the-sage-encyclopedia-of-research-design-2e.
    Look for the Institution login on the top right. Click on that and search for National University.
  • Statistic
    Spatz, C. (Ed.) (2022). Statistic. Encyclopedia of research design. SAGE. https://doi.org/10.4135/9781071812082
    https://sk.sagepub.com/reference/the-sage-encyclopedia-of-research-design-2e.
    Look for the Institution login on the top right. Click on that and search for National University.