discussion board 2 8 DISCUSSION BOARD 21 Discussion Board 2 Interpretation Questions

discussion board 2 8
DISCUSSION BOARD 21
Discussion Board 2
Interpretation Questions
D.2 1
           For categorical data such as low, middle, and high-income, a bar chart would be the most appropriate use of measurement. According to Morgan, when there is nominal data (in this case, income), a bar chart or frequency distribution would be appropriate with nominal data (Morgan et al., 2013). Research also suggests that control charts take into account estimation effects; thus, if the income level is hypothesized to be constantly changing within the participants, one can pinpoint those estimates more easily (Sarmiento et al., 2020). 
           Nominal variables contain three or more non-ordered actual category names or labels (p. 43, 2013). Some examples would include ethnic groups, religious groups, curriculums, and hair D2.3.2. (a)
color. Dichotomous would be two-level variables such as gender or math grades (high versus low) (p. 43, 2013). Ordinal variables are also three or more variables that are ordered but also unequal intervals between the levels that are not normally distributed and are often skewed, such as competence, scales, or mother’s education (p. 43, 2013). Finally, standard scale variables are five or more ordered level groups generally distributed with equal intervals between levels; examples would be SAT math scores, achievements, or height (p. 43, 2013).
D2.3.2. (b)
           It is essential to distinguish between interval and ratio variables in social science because interval scales do not hold zero and can even be below zero. In contrast, ratio variables will never fall below zero (Interval scale vs. ratio scale: the difference? 2021). Therefore, if a research study has below zero values, the researcher will use interval scales; if not, it would be ratio variables.
D2.3.3
           The rule of thumb is that 68% of the data will fall within one standard deviation above and below the mean. This means that roughly 95% of the data will fall between two standard deviations of the mean.
D2.3.4. (a)
           Normal distribution states that under standard customary distribution units’ underneath those units are referred to as z-scores (p. 52, 2013).
D2.3.4. (b)
           A negative z-score of -3 would mean that the raw score is below the mean average.
D2.3.4. (c)
           If a z-score is between -2 and +2, this means that the score is either two or three percent away from the standard deviation. This is important when finding a hypothesis to a research question.
D2.3.5
           According to Morgan, a frequency polygon with nominal or dichotomous data would not be appropriate (p. 49, 2013). To display nominal data, one would either use a bar chart or a frequency distribution.
Abstract
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Discussion Board 2
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[Heading 2]1
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[Heading 5].
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References
Last Name, F. M. (Year). Article Title. Journal Title, Pages From – To.
Last Name, F. M. (Year). Book Title. City Name: Publisher Name.
Footnotes
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Tables
Table 1
[Table Title]
Column Head
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789
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Figures title:
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