Time Series • Time Series Analysis and Components

P2.05 Numerical Description

Practical 2 Time Series Analysis and Components

Quick concept

Compute numerical summaries of a quarterly profit series and relate them to the plot.

Practical / Solution

P2.05 Numerical Description

Problem Statement

Compute numerical summaries of a quarterly profit series and relate them to the plot.

Learning Outcomes

Report mean, median, min, max and standard deviation.
Say what a large standard deviation means for forecasting.

Theory

Numerical description summarises level and spread. For time series, summaries ignore order unless you also compute growth rates or split by season.

Dataset / Data Source

Constructed 8 quarterly profits: 12, 15, 14, 18, 20, 19, 23, 25.

Analysis / Program

import pandas as pd idx = pd.period_range("2024Q1", periods=8, freq="Q") profit = pd.Series([12, 15, 14, 18, 20, 19, 23, 25], index=idx, name="profit") print(profit.describe()) print("Range:", profit.max() - profit.min())

Expected Output

A describe() table for these eight numbers, including mean and std, plus the range 13.

Result / Interpretation

The mean sits near the middle of a rising series, so it is a poor description of the latest level. Spread matters because a wider series is harder to forecast tightly.

Note

A single mean can mislead when the series has a trend. Always pair numbers with a plot.