5 August 2022,
The task that dr. Budi assigned has led me to learn as much about the basics of R, using the data set of pregnancy estriol and birth weight. Here is the list of what I learned:
Basic data analysis in R
- Fivenum: a function that results the minimum, 1st quartile, median, 2nd quartile, and maximum value of a data set. This also serves as a base to determine the structure of boxplot graphic.
- Summary: a function that results the minimum, 1st quartile, median, mean, 2nd quartile, and maximum value of a data set.
Exploratory graphs (visualization) in R
- Boxplot: a graph which visualizes how well the data observations are distributed. Presence of outliers can be a sign of a data that do not distributed well.
- Histogram: a graph which visualizes frequency of data observations and also determines skewness.
- Scatterplot: a graph which visualizes and determines if two vectors/variables are linear or nonlinear. This also determines if the vectors/variables are interconnected or not.
Normality test and normalization in R
- Normality test: a test to confirm whether the data is normally distributed or not. Can be tested using shapiro-wilk test, skewness, q-q plot, or other methods.
- Normalization: a method to reduce the scale of variables, affecting the data distribution.
With these materials, I have tried to apply its basic knowledge to analyze the pregnancy estriol level and birth weight data set that has been given before. The results can be seen in the attachment below: