My group have different opinions towards the following question:

Find the least squares estimate of alpha and beta of the mechanistic growth
model: Y=alpha*(1-beta*e^-x) using the following dataset.
Y 1 1.1 1.39 1.55 1.63 1.86 1.98
X 0 0.1 0.5 0.8 1 2 4

What the question want us to do? What is the answer look like?(We are using excel to do the regression analysis)
Curve fitting? Or just directly do the simple regression by the dataset?

Hi, you have data (one outcome Y and one predictor X) and you have a regression equation with two unknown parameters alpha and beta. Now you use Excel to make a regression fit based on the least squares method and using the regression formula above. The results are estimates for alpha and beta. "Least squares" only means a standard algorithm to find alpha and beta such that the curve fits the data.