For this Discussion, you will examine central tendency and variability based on two separate variables. You will also explore the implications for positive social change based on the results of the data.
To prepare for this Discussion:
- Review this week’s Learning Resources and the Descriptive Statistics media program.
- For additional support, review the Skill Builder: Visual Displays for Categorical Variables and the Skill Builder: Visual Displays for Continuous Variables.
- Review the Chapter 4 of the Wagner text and the examples in the SPSS software related to central tendency and variability.
- From the General Social Survey dataset found in this week’s Learning Resources, use the SPSS software and choose one continuous and one categorical variable Note: this dataset will be different from your Assignment dataset).
- As you review, consider the implications for positive social change based on the results of your data.
Post, present, and report a descriptive analysis for your variables, specifically noting the following:
For your continuous variable:
- Report the mean, median, and mode.
- What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?
- Report the standard deviation.
- How variable are the data?
- How would you describe this data?
- What sort of research question would this variable help answer that might inform social change?
Post, present, and report a descriptive analysis for your variables, specifically noting the following:
For your continuous variable:
- Report the mean, median, and mode.
- What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?
- Report the standard deviation.
- How variable are the data?
- How would you describe this data?
- What sort of research question would this variable help answer that might inform social change?
Post, present, and report a descriptive analysis for your variables, specifically noting the following:
For your continuous variable:
- Report the mean, median, and mode.
- What might be the better measure for central tendency? (i.e., mean, median, or mode) and why?
- Report the standard deviation.
- How variable are the data?
- How would you describe this data?
- What sort of research question would this variable help answer that might inform social change?
Post the following information for your categorical variable:
- A frequency distribution.
- An appropriate measure of variation.
- How variable are the data?
- How would you describe this data?
- What sort of research question would this variable help answer that might inform social change?
Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.
Continuous Variable Analysis:
For the continuous variable, let’s choose “income” from the General Social Survey dataset.
- Descriptive Analysis:
- Mean: The average income.
- Median: The middle value of income when all incomes are sorted in ascending order.
- Mode: The income value that appears most frequently.
- Better Measure for Central Tendency:
- The median might be a better measure for central tendency in this case because income data can often be skewed by extreme values (outliers), and the median is less influenced by outliers compared to the mean. However, considering the symmetry of income distributions in some populations, the mean could also be a good measure.
- Standard Deviation:
- Standard deviation measures the dispersion or spread of the income data around the mean. A higher standard deviation indicates greater variability in incomes.
- Variability of Data:
- The variability of income data would depend on the population being studied. In some populations, income might be highly variable, while in others, it might be relatively consistent.
- Description of Data:
- The income data could be described as positively skewed if most people have relatively low incomes with a few individuals having very high incomes, or it could be symmetrically distributed if incomes are more evenly spread across the population.
- Research Question and Social Change Implications:
- Research questions related to income inequality, poverty alleviation, social mobility, and economic disparities could be addressed using this variable. Understanding income distribution within a population can inform policies aimed at promoting social equity and economic justice.
Categorical Variable Analysis:
For the categorical variable, let’s choose “education level” from the General Social Survey dataset.
- Descriptive Analysis:
- Frequency Distribution: A table showing the count or proportion of individuals in each education category.
- Measure of Variation: Perhaps the range of education levels or the interquartile range could be used as a measure of variation.
- Variability of Data:
- The variability of education levels would depend on the population being studied. In some populations, there might be significant variability with individuals having a wide range of educational attainment levels, while in others, education levels might be more uniform.
- Description of Data:
- The data would describe the distribution of educational attainment within the population, ranging from individuals with no formal education to those with advanced degrees.
- Research Question and Social Change Implications:
- Research questions related to educational access, attainment gaps, educational equity, and the impact of education on various outcomes such as employment, health, and social mobility could be addressed using this variable. Understanding disparities in education can inform policies aimed at improving access to education and reducing educational inequalities, thus promoting positive social change.