Answer:
The y-intercept in the model represents the base salary
Step-by-step explanation:
In regression analysis, the y-intercept refers to the point where a regression line crosses or cuts the y-intercept. At this point, the value of the explanatory variable X is usually 0.
In the model, the explanatory variable x is Ashley's total sales for the year. On the other hand the dependent variable is the annual salary which depends on total sales.
Substituting x with 0 in the regression model yields;
y = 0.2(0) + 25,000
y = 25,000
The y-intercept is thus 25,000 which is simply the salary earned in the absence of sales. This is simply the basic salary.
When you say empirical argument, it means facts gathered and concluded through a series of experimentation and reliable data gathered and not through theory or speculation.
Therefore, a sample size can greatly affect the validity of an empirical argument once proven inaccurate because what we want to see in an empirical argument is the clear-cut reality of what the researchers gathered through meticolous experimentation and not otherwise.
300ml of ethanol is not the same as 300L of ethanol and 2 grams of salt is not 2 kilos of salt. However, if it can be explained thoroughly that a sample size is just a fraction representation of the original, it is wise to create a control subject to compare the data and make it more reliable. Say for example, you wouild like to compare the sun and the earth, make sure to make the models realistically proportional in your miniature globe models.
<span>$200/$375 = 25.9%
your answer is 25.9%</span>
Answer:
Step-by-step explanation:
