29 Jul WHAT IS THE MEAN INCOME AND MEAN NUMBER OF HOURS WORKED?
Research
Question: Does the number of hours worked per week (workweek) predict
family income (income)?
Using
Polit2SetA data set, run a simple regression using Family Income (income)
as the outcome variable (Y) and Number of Hours Worked per Week (workweek)
as the independent variable (X). When conducting any regression analysis, the
dependent (outcome) variables is always (Y) and is placed on the y-axis, and
the independent (predictor) variable is always (X) and is placed on the x-axis.
Follow these steps when
using SPSS:
Open Polit2SetA data set.
Click on Analyze, then click on Regression,
then Linear.
Move the dependent variable (income) in the box
labeled “Dependent” by clicking the arrow button. The dependent variable
is a continuous variable.
Move the independent variable (workweek) into the
box labeled “Independent.”
Click on the Statisticsbutton (right side of
box) and click on Descriptives, Estimates, Confidence
Interval (should be 95%), and Model Fit, then click on Continue.
Click on OK.
Assignment:
Through analysis of the SPSS output, answer the
following questions.
What is the total sample size?
What is the mean income and mean number of hours worked?
What is the correlation coefficient between the outcome
and predictor variables? Is it significant? How would you describe the
strength and direction of the relationship?
What it the value of R squared (coefficient of
determination)? Interpret the value.
Interpret the standard error of the estimate? What
information does this value provide to the researcher?
The model fit is determined by the ANOVA table results (F
statistic = 37.226, 1,376 degrees of freedom, and the p value is
.001). Based on these results, does the model fit the data? Briefly
explain. (Hint: A significant finding indicates good model fit.)
Based on the coefficients, what is the value of the
y-intercept (point at which the line of best fit crosses the y-axis)?
Based on the output, write out the regression equation
for predicting family income.
Using the regression equation, what is the predicted
monthly family income for women working 35 hours per week?
Using the regression equation, what is the predicted
monthly family income for women working 20 hours per week?
Multiple Regression
Assignment: In this
assignment we are trying to predict CES-D score (depression) in women. The
research question is: How well do age, educational attainment, employment,
abuse, and poor health predict depression?
Using
Polit2SetC data set, run a multiple regression using CES-D Score (cesd)
as the outcome variable (Y) and respondent’s age (age), educational
attainment (educatn), currently employed (worknow), number, types
of abuse (nabuse), and poor health (poorhlth) as the independent variables
(X). When conducting any regression analysis, the dependent (outcome) variables
is always (Y) and is placed on the y-axis, and the independent (predictor)
variable is always (X) and is placed on the x-axis.
Follow these steps when
using SPSS:
1. Open Polit2SetC data set.
2. Click on Analyze,then click on Regression,
then Linear.
3. Move the dependent variable, CES-D Score (cesd) into
the box labeled “Dependent” by clicking on the arrow button. The dependent
variable is a continuous variable.
4. Move the independent variables (age, educatn, worknow,
and poorhlth) into the box labeled “Independent.” This is the first
block of variables to be entered into the analysis (block 1 of 1). Click on the
bottom (top right of independent box), marked “Next”; this will give you
another box to enter the next block of indepdent variables (block 2 of 2). Here
you are to enter (nabuse). Note: Be sure the Method box states
“Enter”.
5. Click on the Statistics button (right side of box) and
click on Descriptives, Estimates, Confidence Interval
(should be 95%), R square change, and Model Fit, and then click on
Continue.
6. Click on OK.
Assignment: (When answering all questions, use the data on the
coefficients panel from Model 2).
Analyze the data from the SPSS output and write a paragraph
summarizing the findings. (Use the example in the SPSS output file as a
guide for your write-up.)
Which of the predictors were significant predictors in
the model?
Which of the predictors was the most relevant predictor
in the model?
Interpret the unstandardized coefficents for educational
attainment and poor health.
If you wanted to predict a woman’s current CES-D score
based on the analysis, what would the unstandardized regression equation
be? Include unstandardized coefficients in the equation.
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