Please post 2 or more peer responses
In the response posts, remember to demonstrate you have read and understood the student’s post by taking their discussion to the next level. Do this by:
· Stating why you agree or disagree with your peers’ conclusions on the significance and importance of the data they selected.
· Sharing other information that this change might suggest about that community.
Please be sure to validate your opinions and ideas with citations and references in APA format.
Estimated time to complete: 2 hours
I chose to compare the values of housing between the years 2020 and 2022 for the city of Deltona in FL. In 2020, most homes (1,304,637) were valued between $200,000 and $299,999, with the average single-family home being $212,446 (“Cost of living in Deltona, Florida,” n.d.). However, in 2022, most homes (1,661, 518) were valued $300,000-$499,999, with the average cost of a singular family home being $307,980 (“Cost of living in Deltona, Florida,” n.d.). Therefore, a single-family home raised about $95,534 between 2020 and 2022.
average value of single-family home for 2020 = average value of single-family home for 2022. In other words, the average value of a singular family home in 2021 may have no effect on the average singular family home of 2022. Therefore, stating that the difference is not significant.
The housing value between 2020 and 2022 has a possibility of being significantly different. Many of the homes were valued between $300,000 and $499,999 in 2022 which raised significantly from the max value of $299,999 in 2020. Thus, causing an increased variability of about $200,000 between 2020 and 2022. The null hypothesis would compare the average values of the homes between 2020 and 2022 to test the significance of the values. After data collection is complete, hypothesis testing takes your sample data and evaluates how consistent they are with the null hypothesis. The p-value is a crucial part of the statistical results because it quantifies how strongly the sample data contradict the null hypothesis. When the p-value is less than or equal to your significance level you reject the null hypothesis. On the other hand, when the p-value is greater than your significance level, you fail to reject the null hypothesis (Frost, 2022).
When discussing monetarily value this difference is important as it effects the housing opportunities for individuals. This can cause a domino effect within the community. Higher home cost hinders homeownership among the lower- and middle-income households also increasing rent obligations for those unable to afford buying. If housing accounts for greater share of house income, households will have less to spend on other goods. Therefore, effecting the demand for consumer goods within the community. With a decreased demand for consumer goods, job availability also becomes a concern. One singular issue has now created many other factors impeding economic growth for the community. The economy as a whole would be more productive if housing costs did not act as a significant distortion affecting where people choose to live and work (Hedlund, 2023).
References
Cost of living in Deltona, Florida (average prices in Deltona 2024). Dwellics. (n.d.).
Frost, J. (2022). Null hypothesis: Definition, rejecting & examples. Statistics By Jim.
hypothesis/
Hedlund, A. (2023). Housing affordability – trends, consequences, and policies. The CGO.
affordability-trends-consequences-and-policies/
The characteristics that I picked was analyzing the economical stability in Wisconsin. To specify I compared the employment in Wisconsin. In doing so I utilized the US Census and selected economic characteristics. Starting with the data for the year 2010 and comparing it with the data from 2019. This allowed an examination for the changes in employment rates over nine years. I noticed the employment rates in Wisconsin for 2010 and 2019 were listed on the DP03 form. In 2010, the ACS data stated that the employment rate in Wisconsin was approximately 64.4%. While in 2019, this rate had decreased slightly to 64.0%. This change represents a slight decrease of .4 percentage points over the nine years of comparison. This dataset was picked because, during the Great Recession there was the most important macroeconomic shock to the United States’ economy in generations (Shambaugh, J. 2021). The overall recovery of the Great Recession was slow because of how deeply the recession affected society and the economy.
Was there a difference in the values of your variable?
Yes, there was a slight difference in the values of the variables by .4%.
How would you write the null hypothesis if you wanted to test the differences statistically?
The null hypothesis would be written as;
There is no significant difference in the values of the variable between the two groups.
Does the difference appear to be a significant one? How would you substantiate that?
To determine if the difference is significant, a statistical test would be performed. For example, a t-test or ANOVA. If the p-value is less than the significance level (commonly 0.05), the null hypothesis would be rejected. Which would indicate that the difference is statistically significant.
Is the difference important?
The importance of the difference depends on the context and the variable in question. An example of this would be if the variable is related to health outcomes, even a small difference could be important.
What are the consequences of the change in your values for your community? For example, a significant increase in the number of women never married could affect the birth rate. It could also mean more women are attending college and becoming self-sufficient.
The consequences of the change in values for the community could vary. For example, if the variable is the number of women never married, a significant increase could lead to a lower birth rate and potentially more women pursuing higher education and becoming self-sufficient. This could have broad social and economic impacts, such as changes in workforce demographics and shifts in family structures. Education provides the aim of this research is to explore educational and other environmental, economic and social determinants on poverty (Liu et al., 2021). With that said, stressing the importance of education as it reduces the level of poverty and the role of higher education is seemingly more important in closing the gap of poverty and unemployment.
References
Liu, F., Li, L., Zhang, Y., Ngo, Q. T., & Iqbal, W. (2021). Role of education in poverty reduction: macroeconomic and social determinants form developing economies. Environmental Science and Pollution Research, 28, 63163-63177.
to an external site.
Shambaugh, J. C., & Strain, M. R. (2021). The recovery from the Great Recession: A long, evolving expansion. The ANNALS of the American Academy of Political and Social Science, 695(1), 28-48.
to an external site.
Edited by
Laura Syverson
on Jun 11 at 10:21am
