SPSS part 3
MP 3
Rakan, Sami Ahmad
October 10, 2019
Introduction:
One of the most affective application of statistics is describing data using descriptive statistics and regression. Descriptive is the kind of statics analysis which serves to depict about the data in sorted manner. The measurements is utilized to portray quantitatively about the significant highlights of the data. These rundowns or portrayals can either be graphical or quantitative. (Walpole, 1982). For instance the dataset of the 50 colleges/universities, the data is retrieved from the https://collegescorecard.ed.gov.
Before discussed father the data has following variables.
|
Variables |
|
College enrollment (Y) |
|
X1 = Average Annual Cost |
|
X2 = average salary |
|
X3 = a dummy variable |
|
X4=Graduation Rate |
|
X5=Students Paying Down Their Debt |
|
X6=Students Who Return After Their First Year |
|
X7=Size |
|
X8=Average Years to Graduation |
|
X9=Ratings of the college |
The descriptive summer of the data is give below:
In the multiple regression output we see that all others variable are insufficient except Average Annual Cost.
So the regression between College enrollment and Average Annual Cost is given below:
The R-squared (R2) is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model. For this model the R square is 0.072 which indicates that there is 7% variance for College enrollment variable that's explained by an Average Annual Cost.
Walpole, R. (1982). Introduction to Statistics. (3rd ed.). Prentice Hall Publication.
Downie, N. M. & Heath, R. W. (1965). Basic Statistical Methods (2nd ed.). Harper & Row Publisher
Reid, H. (2013, August). Introduction to Statistics. SAGE Publication.