Ordinary Least Squares - Example With Real Data

Example With Real Data

The following data set gives average heights and weights for American women aged 30–39 (source: The World Almanac and Book of Facts, 1975).

Height (m): 1.47 1.50 1.52 1.55 1.57 1.60 1.63 1.65 1.68 1.70 1.73 1.75 1.78 1.80 1.83
Weight (kg): 52.21 53.12 54.48 55.84 57.20 58.57 59.93 61.29 63.11 64.47 66.28 68.10 69.92 72.19 74.46

When only one dependent variable is being modeled, a scatterplot will suggest the form and strength of the relationship between the dependent variable and regressors. It might also reveal outliers, heteroscedasticity, and other aspects of the data that may complicate the interpretation of a fitted regression model. The scatterplot suggests that the relationship is strong and can be approximated as a quadratic function. OLS can handle non-linear relationships by introducing the regressor HEIGHT2. The regression model then becomes a multiple linear model:

The output from most popular statistical packages will look similar to this:

Method: Least Squares
Dependent variable: WEIGHT
Included observations: 15

Read more about this topic:  Ordinary Least Squares

Famous quotes containing the words real and/or data:

    “A man’s real faith is never contained in his creed, nor is his creed an article of his faith. The last is never adopted. This it is that permits him to smile ever, and to live even as bravely as he does. And yet he clings anxiously to his creed, as to a straw, thinking that that does him good service because his sheet anchor does not drag.”
    —Henry David Thoreau (1817–1862)

    “Mental health data from the 1950’s on middle-aged women showed them to be a particularly distressed group, vulnerable to depression and feelings of uselessness. This isn’t surprising. If society tells you that your main role is to be attractive to men and you are getting crow’s feet, and to be a mother to children and yours are leaving home, no wonder you are distressed.”
    —Grace Baruch (20th century)