Central tendency and variability based on two separate variables
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?
Data Source: General Social Survey (GSS) - Public use data might differ based on access.
Chosen Variables:
- Continuous Variable: Age (in years)
- Categorical Variable: Highest level of education attained (High School, Some College, Bachelor's Degree, Graduate Degree)
Analysis of Continuous Variable: Age
- Mean: This might be a good measure of central tendency, but it can be skewed by outliers (extreme values).
- Median: This might be a better measure here as it represents the middle value, unaffected by outliers (assuming a normal distribution).
- Mode: The mode is likely not very informative in this case, as age is spread across a range of values.
- Standard Deviation: This will tell us how spread out the data is around the mean or median.
- Data Variability: Depending on the standard deviation, the data could be highly variable (large standard deviation) or relatively clustered around the central tendency (small standard deviation).
- Data Description: Knowing the average or median age and variability can help describe the population surveyed (e.g., young, middle-aged, or older population with high or low variability).
- Social Change Research Question: How do educational attainment levels differ across various age groups? This could inform policies targeting education programs for specific demographics.
Analysis of Categorical Variable: Education Level
- Frequency Distribution: This will show the number of respondents in each education category (High School, Some College, etc.).
- Measure of Variation: Chi-Square test can be used to assess if the distribution of education levels differs from what would be expected by chance.
- Data Variability: The data is variable if the distribution of respondents across education levels is not uniform.
- Data Description: The frequency distribution will show the most common education level and how education varies within the sample.
- Social Change Research Question: Are there social or economic factors influencing educational attainment levels? This could inform policies promoting educational equity.
Note: Without access to the specific GSS data, I cannot provide actual values for mean, median, standard deviation, or frequency distribution. However, the explanations above outline the steps involved in analyzing central tendency and variability for the chosen variables.
By analyzing these variables, we can gain insights into the sample population and identify potential areas for social change initiatives. For example, if a significant gap exists between age groups and educational attainment, targeted programs could be developed to address these disparities.