Final answer:
To forecast week 13 using regression historical data is used to create a regression line and the formula derived from the regression analysis applied to week 13 to predict the outcome.
Step-by-step explanation:
To predict the forecast of week 13 using regression forecast, you need to have historical data from the previous weeks. This data is used to generate a regression line which is a statistical method used to model relationships between variables. Typically, you would use a software program or a calculator with regression capabilities to input your data, such as the weekly figures for 12 weeks. the regression analysis would then give you an equation for the regression line, often in the form of y = mx + b where y is the predicted value, m is the slope of the line, x is the time variable (in this case, the week number), and b is the y-intercept.
To forecast for week 13, you simply plug 13 into the equation as the value of x, and calculate the corresponding value of y, which would be the forecast for that week. the precision of this forecast will depend on the fit of the regression model to the historical data. Factors such as the value of the correlation coefficient can help determine this fit. the closer the correlation coefficient is to either -1 or 1, the better the model fits the data.