SPSS Project Regression
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I. Linear Regression
In a research study for the effect of smoking on the infant birth weight, three variables were
recorded, and they are the followings.
 Birth Weight in grams
 Gestation period in weeks
 Mother Smoke or Not
 Mother’s Age
The data is in the file stored in the following address:
http://people.ysu.edu/~gchang/stat/reg_weightgestage_07.sav
Use the linear regression modeling technique to answer the following questions:
1. Make a scatter plot for birth weight versus length of gestation period and a scatter plot
for birth weight versus mother’s age, and describe the relation between each pair of
variables.
[Paste the graphs here!]
[Describe here!]
2. Make a scatter plot for birth weight versus length of gestation period with mother
smoking status as the other categorical factor variable (markers variable). Does the
smoking variable appear to be a significant factor on birth weight?
[Paste the graph here!]
[Describe here!]
3. Run the regression analysis and check the multicollinearity condition using VIF. Are
gestation period in weeks, mother’s age, and mother’s smoking status significant
factors in predicting infant’s birth weight? Does smoking increase the risk of having
low birth weight baby? Is there a multicollinearity problem? (Show the SPSS
coefficient table and interpret.)
[Paste SPSS output table here!]
[Describe here!]
4. Estimate the average weight of infants from mothers aged 35 who smoke and have a
gestation period of 37 weeks with a 95% confidence level. [Use a model with all
predictor variables mentioned in 3.]
5. Estimate the weight of infant from mother aged 35 who smoke and has a gestation
period of 37 weeks with a 95% confidence level. [Use a model with all predictor
variables mentioned in 3.]
6. Find the linear regression equation for predicting the average infant birth weight using
only the significant predictor variables.
[Write the linear regression equation here!]
7. Perform a two independent samples t-test to see if there is significant difference
between the average infant birth weights for mothers who smoked versus not smoked.
Does the result contradict with the result in 3? If yes, why?
[Paste the SPSS output on two independent samples t-test here!]
II. Logistic Regression on Risk Behavior Study
In a Risk Behavior Survey study on college students the following variables were observed:
Risk Behavior Variable: Wear seatbelt while last time driving a car
Risk Factor Variables:
 Sex (0=Female, 1=Male)
 Race (1=White, 2=Black, 3=Other)
 Live on campus (0=Off Campus, 1=On Campus)
The data is in the following address:
http://people.ysu.edu/~gchang/stat/log_YRB_07.sav
Use the logistic regression technique to answer the following questions: (Do not use stepwise
regression.)
1. Report the frequency and percentage distribution for each of the four variables
observed in this study.
2. Find the significant factor(s) that affects whether students wearing seatbelt or not.
[Paste the SPSS output containing parameter estimation information here!]
3. Use the odds ratios to explain how each of the significant factors affecting the risk
behavior.
4. Use the logistic regression model to estimate the probability of a randomly selected
white male student and living off campus that will not wear a seatbelt.