andrew wrote: » Which exact bits are you having trouble interpreting? Which bit of that excel result do you understand?
andrew wrote: » To simplify your output there, what that excel spreadsheet translates to is an equation which says: (child's income) = 7.84 + 0.3*(ability) + 0.28*(family income) This makes it slightly easier to interpret. I don't wanna give you the answer so Now what you need to think about is:What does the number before 'ability' and 'family income' actually mean? What does the intercept mean? Which number (coefficient) is the one you care about Does it have the sign you'd expect it to have (positive or negative) given the theory you're working from? And most importantly, is it stastically significant? For this, you look at the t-value or p-value associate with the coefficient; is sufficient for your confidence level?
freeze4real wrote: » Hi again sorry for late reply. I don't understand this but I will guess. The number before ability is the slope and the one after family income is the intercept. They 're both positive. I'm trying to interpret this, If your ability goes up by .301 your family income goes up by 0.27 as your income depends on the ability of doing the job. Am I far off ?
andrew wrote: » The first number, without any coefficient, is the intercept. It tells you how much a person would earn, if the other two coefficients were 0 (according to the data you have). Whatever book you're using should a have a specific bit on interpreting the numbers in front of the coefficients, but to offer some explanation: Remember, the point of a regression is to try to figure out what factors affect some other factor of interest. The factor you're interested in is called the dependant variable, and the other factors which you think might affect the dependant variable are the independent variables. In your case, child's income is the dependant variable, and family income and ability are the independent variables. I figure you probably already have an idea of this already, all you need to do now is relate this to the equation above. Imagine, then, the output of that equation when you change (ability) by a single unit; you said that that affects (family income). But how? According to that equation (and regressions in general), if you just increased (ability) by 1, what changes isn't (family income), it's the dependent variable (child income). I let you figure out exactly how much is changes by. But that's the point of the regressions, you're creating an equation which lets you figure out what happens to the dependent variable, when you change just one if the independent variables. The independent variables don't affect one another, that's why they're independent. The same goes for changing (family income) by a single unit too. Try to figure out how much the dependent variable changes when you just increase family income by $1. As with (ability) above, finding out how the dependent variable changes is just a matter of using multiplication to see how the dependent variable changes. Once you've done that, then you'll need to see whether the coefficients you've obtained are statistically significant; use the t and/or p values for this.
Helpneeded86 wrote: » Im a bit confused by this and would appreciate some help. Y= B0 + B1(X1) + B2(X2) + B3(X3) Lets say B0 is the intercept is that correct? B1, 2 and 3 are the independent variables. Assuming i have the above correct what confuses me is what is X1,2,3? Also assuming the following question Write out the appropriate Demand/Sales equation and comment on the value of the coefficients of the individual terms in the regression equation. You should also describe what each term means with respect to the overall demand/sales for/of coffee. Is the above equation what i should be writing out Y= 7.84 + 0.301(X1) + 0.27(X2) What figures would you fill in for X is what still confuses me.
andrew wrote: » X1 and X2 in the second equation are the factors which might affect the demand for coffee. The numbers in front of X1 and X2 tell you the direction of the effect these factors have (can be positive or negative) as well as the magnitude of the effect.
b Write out the appropriate Demand/Sales equation and comment on the value of the coefficients of the individual terms in the regression equation. You should also describe what each term means with respect to the overall demand/sales for/of coffee.
Helpneeded86 wrote: » I need to study a little more about how to comment on each factor. I understand how the price has a huge effect but on a negative confuses me i assume this means that when they raise the price of coffee it has a negative impact on sales. The other two factors have very little bearing on sales.
