Simple Linear Regression

03_data
20160102

# House price data

The data used is this article is the following, actual house price data sampled on 2016-01-02. The x vector has the surface area in square meters, and the y vector contains the corresponding price in kilo-EURO's.

``````x_v= [300.,245.,170.,261.,240.,200.,217.,55.,110.,256.,90.,245.,200.,
139.,260.,300.,195.,153.,138.,185.,170.,66.,100.,160.,110.,197.,
135.,214.,259.,196.,216.,161.,100.,130.,250.,120.,230.,122.,120.,
260.,175.,200.,100.]

y_v= [625.,335.,479.,500.,490.,325.,495.,172.,325.,395.,225.,630.,325.,
425.,425.,625.,520.,248.,258.,349.,269.,245.,249.,275.,299.,525.,
560.,345.,630.,399.,445.,420.,240.,395.,550.,225.,635.,320.,275.,
395.,420.,430.,239.]``````
``````x_v= c(300,245,170,261,240,200,217,55,110,256,90,245,200,139,260,300,
195,153,138,185,170,66,100,160,110,197,135,214,259,196,216,161,
100,130,250,120,230,122,120,260,175,200,100)

y_v= c(625,335,479,500,490,325,495,172,325,395,225,630,325,425,425,625,
520,248,258,349,269,245,249,275,299,525,560,345,630,399,445,420,
240,395,550,225,635,320,275,395,420,430,239)``````

## Scatterplot

``````    import matplotlib.pyplot as plt

plt.scatter(x_v, y_v)
plt.ylabel('kEUR')
plt.xlabel('square meters')
plt.title('House Price')
plt.show()``````

Notes by Data Munging Ninja. Generated on nini:sync/20151223_datamungingninja/linregsimple at 2016-10-18 07:18