04 Apr Each student will post an Excel spreadsheet to Canvas that provides original data organized in a chart, and displays data in a
Please see attached documents.
Instructions :
Each student will post an Excel spreadsheet to Canvas
that provides original data organized in a chart, and
displays data in a graph. Guidelines for data
collection:
Data must be publicly available, or, you must
have permission in writing to share that data
publicly.
Projects are not going to be submitted to the IRB
for approval, thus must focus on publically
available data or surveys.
Sources must be properly cited.
Do not simply use statistics provided in a
published study.
No experiments on humans or animals are
permitted.
Collect data based off of Document SEA PROPOSAL. Hypothesis test needed to be performed will be a comparison of proportions of children who take and do not take ascorbic acid.
Rubric Attached.
Example attached for how data collection should look and be explained.
1
Sea Proposal
Shy Phillips
Wilmington University
Inferential Statistics
March 13, 2022
The effectiveness of Ascorbic acid in preventing or curing the common
Common cold happens to be the most frequent irresistible infection in people. The average individual gets one a few times each year. Interestingly enough, ascorbic acid has frequently been professed to be a viable treatment through the years. However, this belief has not been shared by official bodies, authorities on nutrition, and physicians. This means that a hypothesis can be used to analyze the hypothesis.
I am interested in this question because of the controversies that have been around the subject since around when the then Nobel prize champ Linus Pauling promoted the hypothesis that ascorbic acid could aid treat colds. For this reason, I chose a hypothesis that focuses on analyzing whether or not ascorbic acid is effective in preventing or curing a common cold. The population to be looked into will be children worldwide aged between one and 12. According to Gunnars, for instance, "a supplemental dose of 1–2 grams was enough to shorten the duration of a cold by 18% in children, on average(Gunnars, 2018)." The latter hypothesis raises curiosity on the effectiveness of Ascorbic acid in preventing or curing a common cold, especially around children.
I will use simple random sampling. It is one of the most incredible probability examining methods that aid in saving resources and time. The former is a solid strategy for acquiring data where each individual from a populace is picked arbitrarily, just by some coincidence. Every individual has a similar likelihood of being decided to be part and parcel of a sample. Two hypotheses also determine the method; a) Null hypothesis: children given ascorbic acid are not likely to suffer from the common cold during the flu season. Alternative hypothesis: Children given ascorbic acid are less likely to suffer from the common cold during the flu season. The sample children will be divided into two, those taking ascorbic acid and those taking a placebo during the cold season. Besides, the data will also be collected through assessment of previous research and trials conducted on the research question.
A confounding variable that may limit the study is that there is no scientific evidence that justifies that ascorbic acid may prevent or cure a cold; it is instead a bunch of hypotheses that may deter the full participation of the research population and sample. There is also a belief that the common cold is incurable and it may come and go as it pleases, and the only that can assist is by dressing warmly and drinking home water.
I will choose the visual representation of information because information seen can never be forgotten. A bar chart is a graph that will suit perfectly with the research because it is perfect for plotting information assembled over a certain period. Plus, it is also the easiest when it comes to interpretation.
The type of analysis that I will perform will be the Inferential examination. It can decide and foresee the best outcomes by testing hypotheses of various subjects taken from gathering subjects. In this case, it will result from the previous research trials and investigations conducted together with that of children who will be offered ascorbic acid during the flu season compared to those given a placebo. A p-value, described as a probability that a notable difference could have happened, will also be used. It is (Emmert-Streib & Dehmer, 2019).
References
Emmert-Streib, F., & Dehmer, M. (2019). Understanding statistical hypothesis testing: The logic of statistical inference. Machine Learning and Knowledge Extraction, 1(3), 945-961.
Gunnars, K. (2018, April 24). Can vitamin C prevent or cure colds? Healthline. https://www.healthline.com/nutrition/does-vitamin-c-help-with- colds#TOC_TITLE_HDR_2
,
Running head: AGE CORRELATION TO COLLEGE EDUCATION 1
AGE CORRELATION TO COLLEGE EDUCATION
2
Age Correlation To College Education Analysis
BJ
MAT308
Wilmington University
Research Question and Relevance
Every year in the United States, the cost for a higher education continues to increase while wages remain stagnant. Along with this, more employers are now requiring a Bachelor’s degree for employment. (Hess, 2019) As a current student going for my own Bachelor’s degree and an individual that would like to help high school students pursue higher education, I was curious as to whether or not people in the United States have been more or less likely to pursue a Bachelor’s degree. Are employers pushing people to get degrees? Or is the higher cost of a degree making it less obtainable to individuals? To find answers to these questions I asked, Are Baby Boomers (individuals born between 1944-1964) more likely to have a Bachelor’s degree compared to Generation X (individuals born between 1965-1979)? This will determine if there is a steady increase or decrease in obtaining a higher education, or no changes at all.
Data Description and Data Collection
The two populations studied were both Baby Boomers (born between 1944-1964) and Generation X (born between 1965-1979). I chose 30 individuals from each group to study for a total of 60 participants. (n=60) I conducted the survey myself, by sending a Google Survey to individuals I knew of these age groups asking the year they were born, and if they have a Bachelor’s degree or not. I used cluster sampling by surveying these two groups and randomly selecting answers among them. I may have experienced sampling bias throughout my collection as I have only sent out the survey to individuals I know and their friends. Because I am not able to accurately collect data on everyone in the country, it may not be the most accurate data to represent everyone in these age groups. Doing a test in another part of the country or even another city, may yield different results.
Data Organization
The data I collected can be seen in Table 1 showing how many of the Generation X and Baby Boomer Generation individuals have a Bachelor’s Degree. Figure 1 represents that data in a Histogram.
Table 1
Comparing Education Level with Age
|
Cluster Sampled |
Total # of Individuals |
|
Generation X Individuals with a Bachelor’s Degree |
16 |
|
Generation X Individuals without a Bachelor’s Degree |
14 |
|
Baby Boomer Generation Individuals with a Bachelor’s Degree |
11 |
|
Baby Boomer Generation Individuals without a Bachelor’s Degree |
19 |
Figure 1
Comparing Education Level with Age
Data Analysis
In order to compare the level of Bachelors degrees obtained between both Generations, I performed a Test of Independence to determine a correlation between the two. (α = 0.05, DF = 1) My hypotheses for this test were as follows: Ho: Education Level is independent to Age.
Ha: Education level is dependent to Age.
Table 2 shows my contingency table used for the Test of Independence. The test yielded a test statistic of 1.6835 and a p-value of 0.1945. The p-value is higher than the level of significance, 0.05. Therefore I do not reject Ho, and stick with the hypothesis that education level is independent of age.
Table 2
Contingency Table
|
With Bachelors Degree |
Without Bachelors Degree |
Row Total |
|
|
Generation X |
16 |
14 |
30 |
|
Boomer Generation |
11 |
19 |
30 |
|
Column Total |
27 |
33 |
60 |
My descriptive statistics for all of the ages are shown in Table 3. The mean age for all participants in this study is 58.96 or rounded up, 59. The Median age was 60, this along with the mean could show that a majority of participants leaned towards being in the older side of their respective groups. The Standard deviation is 12.06, showing how the data is spread out.
Table 3
Descriptive Statistics
|
Mean |
58.95 |
|
Median |
60 |
|
Mode |
66, 45, 50, 55, 65, 70 |
|
Standard Deviation |
12.06 |
|
Range |
38 |
Conclusions
This data has shown that there is in fact no clear correlation shown by my data that age and the likelihood of obtaining a Bachelors degree are dependent on each other. Overall, this means that the rising increase of college education may not be deterring individuals from going to school to obtain their degree. Whether or not this changes with future Generations, would be an interesting test to do in the future to see if this conclusion still holds. Going forward it would also be beneficial to see if my results still stand using census data, and examining the population as a whole, compared to my small sample of individuals I know.
References
Hess, A. J. (2019, December 13). The cost of college increased by more than 25% in the last 10 years-here's why. Retrieved December 03, 2020, from https://www.cnbc.com/2019/12/13/cost-of-college-increased-by-more-than-25percent-in-the-last-10-years.html
