Prev Next

R Statistics Intro

R provides a wide range of statistical tools and functions for data analysis, including descriptive statistics, inferential statistics, and regression analysis. Understanding basic statistical concepts is essential for working with data in R.

Key Topics

Descriptive Statistics

Descriptive statistics summarize and describe the main features of a dataset, such as the mean, median, mode, and standard deviation.

# Calculating mean, median, and standard deviation
data <- c(10, 20, 30, 40, 50)

mean_value <- mean(data)
median_value <- median(data)
sd_value <- sd(data)

print(mean_value)
print(median_value)
print(sd_value)

Output:

[1] 30
[1] 30
[1] 15.81139

Code Explanation: The mean(), median(), and sd() functions are used to calculate the mean, median, and standard deviation of the data.

Inferential Statistics

Inferential statistics make inferences about a population based on a sample, using techniques such as hypothesis testing and confidence intervals.

Example content for inferential statistics will be covered in advanced topics.

Key Takeaways

  • Descriptive statistics summarize data using measures like mean and standard deviation.
  • Inferential statistics allow making predictions and testing hypotheses.
  • R has built-in functions for both descriptive and inferential statistics.
Prev Next