Knowing SPSS (Statistical Package for the Social Sciences)
Always have handouts in class
Have a calculator
Working independently on exams
Review of First Stats Course
What are the different types of measurement?
What is correlational analysis
Interpret the following findings:
In a study that examined the relationship between number of days present in school and students’ sense of belonging among 135 high school students the following Pearson Correlation statistics was obtained:
The relationship between time on task and obtaining a grade of C+ or lower was found to be r= -.32; p <= .048 for 50 students in an alternative education program for disruptive students.
What are generalized least square models?
Generalized least square models are models that seek to minimize differences between what we observe and what we calculate.
These models are able to accomplish this, by fitting the data such that the squared deviations between observed and fitted data are minimized.
Refer to example on the board-
Techniques to be Studied
Regression (Simple, multiple, hierarchical)
Analysis of Variance (one-way)
Univariate Analysis of Variance to include Analysis of Covariance
Possibly- Chi- Square
History- in France, applied to the study of astronomy- orbits of bodies around the sun (least squares method)
Term regression coined in the 19 th C to describe a biological phenomenon- children of exceptional individuals tended to be less intelligent than their parents- Darwin’s cousin Francis Galton- “regression towards mediocrity”. Work later extended by Pearson and Yukle
Assumptions of Regression
Sample must be representative of the population.
The dependent variable must be continuous.
The independent variables must be linearly related but not strongly
The independent variable should be continuous although categorical variables can be used.
Values of the independent variables are normally distributed
The Basic Regression Model
Predicted Y= a+ B1(X1)+ B2(X2)……..error
Where B1 represent the impact of X1 on Y
a represents the constant or the intercept.
Y is our outcome variable
X is our independent variable
What do the terms mean?
B is called the slope or the regression coefficient. It is the change in the dependent variable for a unit change in x or the predictor variable
Example of slope
16 years 20,000
18 years 20, 500
20 years 21,000
22 years 21,500
24 years 22, 000
Questions that can be asked in regression
What is the impact of the predictor (independent) variables on the outcome (dependent variable)?
Is the impact significant?
Is the regression model significant?
What percent of the variance in the outcome variable is explained by the predictor (s) variable (s).