Hi, I'm trying to fit an equation:

starting_salary= (intercept+SEX*B0) +B1*GPA  +B2* METRICS

(metrics,sex are  dummy variables, either 0 or 1) to see how sex coefficient affects the intercept ( how it affects starting_salary)

(later on I  want to see how metrics affects starting_salary for either sex=1 and sex =0 .. anyways I disgress) 

STARTING_SALARY :=:  

GPA:=:      

METRICS: =;  

I'm trying to do a least square estimation

with(plots);

q := array([892., 1012., 1060., 987., 680., 739., 809., 1275., 946., 874., 720., 1096.]);

p := array([1.23, 1.15, 1.10, 1.20, 1.35, 1.25, 1.28, .99, 1.22, 1.25, 1.30, 1.05])

lnx := array([seq([ln(p[t])], t = 1 .. 12)]);

lny := array([seq([ln(p[t])], t = 1 .. 12)]);

pointplot({seq([ln(p[t]), ln(q[t])], t = 1 .. 12)}, symbol = circle, axesfont = [TIMES, 14], labels = [x = ln(p), y = ln(q)])

Hi, I have 2 sets of data:

P := array([1.23, 1.15, 1.10, 1.20, 1.35, 1.25, 1.28, .99, 1.22, 1.25, 1.30, 1.05]);

Q := array([892, 1012, 1060, 987, 680, 739, 809, 1275, 946, 874, 720, 1096]);

p=P(t), q=Q(t) i.e. both p & q are a function of parameter t  t=1..12

2 functions: 

x=ln(p)

y=ln(q)

I'm trying to display x against y , ie x=ln(p) on the horizontal axis, y=ln(q) on the vertical