Fundamentals of statistics

Statistics is composed of various elements that work together in collecting, analyzing and interpreting data. To understand the fundamentals of statistics, let's consider a simple example - Imagine you have a bag of colored marbles, and you want to know the proportion of each color in the bag. You randomly pick some marbles and count how many of each color you have.

Statistics starts with data collection, which involves gathering information or observations. In our example, it's the process of picking marbles and recording their colors. The data collected forms the basis for analysis.

Next, we move on to data analysis. This step involves organizing, summarizing, and exploring the data to uncover patterns and insights. For instance, we can calculate the frequencies of different colors or create visual representations like bar charts or pie charts to see the proportions.

Statistics

Descriptive vs Inferential statistics

Descriptive statistics summarizes and describes data, providing an overview of its characteristics. It includes measures of central tendency and variability. Inferential statistics, on the other hand, allows us to make inferences and predictions about a larger population based on a sample. It involves using statistical techniques to analyze sample data and draw conclusions about the population

In essence, descriptive statistics describes the data we have, while inferential statistics helps us make predictions and draw conclusions beyond the observed data. Imagine you want to know the average height of students in your school. You measure the heights of a few students and get the following data:

data: 150 cm, 160 cm, 165 cm, 170 cm, 175 cm. 

Now, let's explore two types of statistics (descriptive and inferential) using the data above.

Descriptive Statistics

Descriptive statistics helps us understand the main characteristics of the data without making any generalizations beyond the sample we have. In our example, we can calculate the mean (average) height of the students, which is

(150 + 160 + 165 + 170 + 175) / 5 = 164 cm

This provides us with a summary of the data and helps us understand the typical height of the students in our sample.

Inferential Statistics

Inferential statistics allows us to draw conclusions and make predictions about the whole group based on the observed sample. For instance, we can use inferential statistics to estimate the average height of all students in the school by taking a random sample and calculating the mean height of that sample. This estimate can then be used to make inferences about the entire student population.

➡️ In the next lesson, we'll be looking more deeper into descriptive statistics 🎯.