Assignment on Statistical Inference (PDF)

STATISTICS

Table of Contents
INTRODUCTION...........................................................................................................................1
Q.1 Statistical inference topic.....................................................................................................1
Q.2 Simple linear regression model............................................................................................2
Q.3 Multiple linear regression model .......................................................................................10
CONCLUSION..............................................................................................................................11
REFERENCES..............................................................................................................................12

INTRODUCTION
According to this particular project which is related with real estate market in non-capital
cities and towns safe-as House real estate and wide national real national estate of the company.
The analysis is done from taking sample size and location with set price data from another town
and city. There are certain tools and techniques use for data analysis is being done in effective
manner.
Q.1 Statistical inference topic
Means
Case Processing Summary
Cases
Included Excluded Total
N Percent N Percent N Percent
V55 125 51.4% 118 48.6% 243 100.0%
V57 125 51.4% 118 48.6% 243 100.0%
Case Processing Summary
Cases
Included Excluded Total
N Percent N Percent N Percent
V55 125 51.4% 118 48.6% 243 100.0%
V57 125 51.4% 118 48.6% 243 100.0%
From the above analysis, it has been determine that total mean value of prices range of
samples A in accordance with the location of state for total number of 125 residential properties
for sale in each samples. By the help of reliable data analysis, it has been seen that there is 51.4%
of total average collected during the time.
Graph
1

Q.2 Simple linear regression model
Regression
Sample 0 (Regional city 1)
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .737a .543 .539 38.415
a. Predictors: (Constant), V9
Model Summary
2