如何使用MySQL数据库进行预测和预测分析？

CREATE TABLE sales (
    id INT AUTO_INCREMENT PRIMARY KEY,
    date DATE,
    product_name VARCHAR(255),
    quantity INT,
    price DECIMAL(10,2)
);

INSERT INTO sales (date, product_name, quantity, price)
VALUES
    ('2020-01-01', 'product1', 100, 10.99),
    ('2020-01-02', 'product2', 200, 20.99),
    ('2020-01-03', 'product3', 300, 30.99),
    ('2020-01-04', 'product4', 400, 40.99),
    ('2020-01-05', 'product5', 500, 50.99);

CREATE TABLE sales_regression (
    id INT AUTO_INCREMENT PRIMARY KEY,
    coefficient DECIMAL(10,2),
    intercept DECIMAL(10,2)
);

INSERT INTO sales_regression (coefficient, intercept)
SELECT
    (n * SUM(x * y) - SUM(x) * SUM(y)) / (n * SUM(x * x) - SUM(x) * SUM(x)),
    (SUM(y) - (n * SUM(x * y) - SUM(x) * SUM(y)) / (n * SUM(x * x) - SUM(x) * SUM(x)) * SUM(x)) / n
FROM (
    SELECT
        @row_number := @row_number + 1 AS n,
        quantity AS x,
        price AS y
    FROM
        sales, (SELECT @row_number := 0) AS t
    ORDER BY
        date
) AS t;

SELECT 
    '2020-01-06' AS date,
    coefficient * 600 + intercept AS predicted_sales
FROM
    sales_regression;

SELECT
    date,
    AVG(price) OVER (ORDER BY date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS moving_average
FROM
    sales;