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COURSE: DATA SCI 101 CRN:21849
PROFESSOR: Dr. Torres Aarong
DESCRIPTION: Introduction, clean dataset, perform EDA, utilize functions, create a summary table or a visualization, and conclusion.
TITLE: PROJECT 1 - “babies_crawl”
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A. Introduction: (1-2 paragraphs):
QUESTION: Is there a correlation between temperature to the average age babies start to crawl?
The dataset I am importing is titled, “babies_crawl.” I collected my dataset from the OpenIntro.org Data Sets website. The dataset includes 5 variables. The first column is title birth_month, the month a baby was born. Second is avg_crawling_age, the average age babies start crawling. Third is sd, for standard deviation. Forth is n, numbers of babies represented for each month. The fifth and last variable is temperature, the average temperature outside when babies were six months of age.
Parts of the dataset necessary to answer my question are the variables, avg_crawling_age and temperature. Avg_crawling_age represent the average age babies in a particular group start crawling and temperature is the average temperature outside when babies were six months of age. With these variables I can find if there is a correlation between temperature to the average age babies start to crawl.
B. Data Analysis (1 paragraph and 3-5 chunks of code):
The type of data analysis I will perform are summary and mean. I chose mean because we are comparing temperature to the average age babies start to crawl, in other words the mean. I then chose summary to gain more insight on the differences in the dataset. The plot I will generate to address if there is a relationship between temperature to the average age babies start to crawl is a scatter plot because it is the best to see a correlation between the variables.
summary(babies_crawl)## birth_month avg_crawling_age sd n temperature
## April :1 Min. :28.58 Min. :5.710 Min. :21.00 Min. :30.00
## August :1 1st Qu.:30.35 1st Qu.:6.925 1st Qu.:26.75 1st Qu.:36.00
## December:1 Median :32.08 Median :7.185 Median :34.00 Median :50.00
## February:1 Mean :31.77 Mean :7.218 Mean :34.50 Mean :50.25
## January :1 3rd Qu.:33.36 3rd Qu.:7.725 3rd Qu.:44.00 3rd Qu.:63.75
## July :1 Max. :33.83 Max. :8.330 Max. :49.00 Max. :73.00
## (Other) :6x <- select (babies_crawl, temperature, avg_crawling_age)
mean(x$avg_crawling_age) ## [1] 31.77167summary(x)## temperature avg_crawling_age
## Min. :30.00 Min. :28.58
## 1st Qu.:36.00 1st Qu.:30.35
## Median :50.00 Median :32.08
## Mean :50.25 Mean :31.77
## 3rd Qu.:63.75 3rd Qu.:33.36
## Max. :73.00 Max. :33.83plot(x$temperature, x$avg_crawling_age)
C. Conclusion and Future Directions (1-2 paragraphs):
Based on the findings, there is a strong inverse correlation between temperature to the average age babies start to crawl. The results of the findings show that the warmer the temperature is, the younger the crawling age begins. Vice versa, the colder the temperature is the older the crawling age begins. Future research could consider if seasons have any affects on when crawling age begins or if it is solely based off of temperature.
REFERENCE(S)
Benson, J. B. (1993). Infant locomotion: Development of crawling. Data retrieved from OpenIntro R Package (openintro). URL: https://www.openintro.org/data/index.php?data=babies_crawl