Weighted Moving Average Calculator

The weighted moving average can be computed easily with our simple efficient weighted moving average calculator. Weighted moving average or WMA is a technique used to smooth and analyze time series data by assigning different weights to each data point within a specified period. WMA allows for more flexibility by emphasizing some data points more than others. This method helps in highlighting trends and reducing the impact of noise or irregularities in the data.

Here are some important applications of the Weighted Moving Average (WMA), highlighting its effectiveness in trend analysis, forecasting, quality control, and signal processing.
• Trend Analysis: WMA helps in identifying and analyzing trends in data by giving more importance to recent observations, making it useful in various fields such as economics and finance.
• Forecasting: Used in forecasting models to predict future values based on the weighted importance of historical data points, improving the accuracy of predictions.
• Quality Control: Applied in quality control processes to monitor and analyze production data, with more recent data being weighted more heavily to detect issues promptly.
• Signal Processing: Employed in signal processing to smooth signals and reduce noise by giving more weight to recent measurements.

Here are weighted moving average examples to calculate weighted moving average (WMA), across different scenarios to provide a clearer understanding of trends within the data.
Example 1: Calculating Weighted Moving Average of Time Spent on Activities
Data: 2 hours on homework, 3 hours on sports, 1 hour on reading, 4 hours on leisure, 2 hours on hobbies
Weight: 4, 1, 5, 2, 3
Number of Consecutive Points to Average: 2
Weighted Average: 2.2 hours, 1.33 hours, 1.85 hours, 2.8 hours
Example 2: Weighted Moving Average of Weekly Temperatures
Data: 65°F, 70°F, 75°F, 80°F, 85°F
Weight: 1, 2, 3, 4, 1
Number of Consecutive Points to Average: 4
Weighted Average: 75°F, 77°F
Example 3: Weighted Moving Average of Monthly Expenses
Data: January: $200, February: $220, March: $240, April: $260, May: $280
Weight: 2, 3, 1, 4, 5
Number of Consecutive Points to Average: 3
Weighted Average: $216.66, $242.5, $268
Example 4: Weighted Moving Average of Daily Sales
Data: $100, $120, $90, $110, $130, $120, $125
Weight: 2, 3, 1, 4, 5, 3, 1
Number of Consecutive Points to Average: 5
Weighted Average: $116, $118.75, $118.92
Example 5: Weighted Moving Average of Daily Steps
Data: 8000 steps, 8500 steps, 9000 steps, 9500 steps, 1308 steps, 1000 steps
Number of Consecutive Points to Average: 2
Weight: 1, 2, 3, 4, 2, 3
Weighted Average: 8333.33 steps, 8800 steps, 9285.71 steps, 6769.33 steps, 1123.2 steps