1. The following model is a simplified version of the multiple regression model used by Biddle and Hamermesh (1990) to study the tradeoff between time spent sleeping and working and to look at other factors affecting sleep: sleep = Bo + B1totwrk+ B2educ + B3age + u, where sleep and totwrk (total work) are measured in minutes per week and educ and age are measured in years. (a) If adults trade off sleep for work, what is the sign of B1? (b) What signs do you think 32 and B3 will have? (c) Using the data in SLEEP75.csv, the estimated equation is sleep = 3638.25 - 0.148totwrk - 11.13educ+2.20age, n = 706 R = 0.113. If someone works five more hours per week, by how many minutes is sleep predicted to fall? Is this a large tradeoff?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
![1. The following model is a simplified version of the multiple regression model used by Biddle and
Hamermesh (1990) to study the tradeoff between time spent sleeping and working and to look
at other factors affecting sleep:
sleep = Bo + B1totwrk + Bzeduc + B3age + u,
where sleep and totwrk (total work) are measured in minutes per week and educ and age are
measured in years.
(a) If adults trade off sleep for work, what is the sign of 31?
(b) What signs do you think 32 and B3 will have?
(c) Using the data in SLEEP75.csv, the estimated equation is
sleep = 3638.25 – 0.148totwrk – 11.13educ + 2.20age,
n = 706
R = 0.113.
If someone works five more hours per week, by how many minutes is sleep predicted to fall?
Is this a large tradeoff?
(d) Discuss the sign and magnitude of the estimated coefficient on educ.
(e) Would you say totwrk, educ, and age explain much of the variation in sleep? What other
factors might affect the time spent sleeping? Are these likely to be correlated with totwrk?
2. Using the same data of previous problem (SLEEP75.csv), we obtain the estimated equation
sleep = 3840.83 – 0.163totwrk – 11.71educ - 8.70age +0.128age? + 87.75male,
(235.11)
(.018)
(5.86)
(11.21)
(.134)
(34.33)
n = 706,
R2 = 0.123,
R = 0.117
The variable sleep is total minutes per week spent sleeping at night, totwrk is total weekly minutes
spent working, educ and age are measured in years, and male is a gender dummy.
(a) All other factors being equal, is there evidence that men sleep more than women? How
strong is the evidence?
(b) Is there a statistically significant tradeoff between working and sleeping? What is the
estimated tradeoff?
(c) What other regression do you need to run to test the null hypothesis that, holding other
factors fixed, age has no effect on sleeping?
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