Analyzing Coronavirus Deaths in Relation to Hospital Bed Availability and Household Income

1. What variables are needed for analysis in this assignment and how should the data be organized?

Data needed for this analysis includes the number of hospital beds per 10,000 people, the number of deaths from the coronavirus, and the average household income, all aggregated at the state level. The data should be organized in an Excel spreadsheet.

Variables for Analysis

Three variables are required for this analysis:
  1. The number of hospital beds per 10,000 people
  2. The number of deaths from the coronavirus
  3. The average household income

Data Organization

To begin the analysis, the data for each variable should be compiled and organized in an Excel spreadsheet. Each state's data should be listed with the corresponding values for hospital beds, coronavirus deaths, and household income. This organization will facilitate further analysis and visualization of the data.

2. What should be done to analyze the correlation between coronavirus deaths and hospital bed availability as well as household income?

Scatter plots should be created to visualize the correlation between the number of deaths from the coronavirus and the number of hospital beds per 10,000 people, as well as the average household income.

Correlation Analysis

Creating Scatter Plots: To analyze the correlation, two scatter plots should be generated: one depicting the relationship between coronavirus deaths and hospital beds, and the other showing the relationship between coronavirus deaths and household income. These plots will help in identifying any patterns or correlations between the variables. On the scatter plots, the points will indicate the data points for each state, allowing for observation of potential relationships between coronavirus deaths, hospital bed availability, and household income. By visually examining the plots, patterns may be discerned that suggest a positive correlation, negative correlation, or no correlation between the variables.

3. How can the observed patterns in the scatter plots be confirmed?

Two simple regression analyses should be run to confirm the patterns observed in the scatter plots. These analyses will provide statistical evidence of the relationships between the variables.

Regression Analysis

Confirmation of Patterns: Following the observation of patterns in the scatter plots, regression analyses should be conducted to confirm the relationships between coronavirus deaths, hospital beds, and household income. The regression analyses will provide numerical values that indicate the strength and direction of the relationships. The observed patterns may be confirmed through regression analyses that show whether there is a positive correlation, negative correlation, or no correlation between the variables. Factors such as socioeconomic conditions, healthcare infrastructure, and other variables may influence the outcomes of the regression analyses.
← High voltage transmission lines the key to efficient power distribution Unleash your potential understanding stress in materials →

More Posts: