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Moderation

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Running head: MULTIPLE REGRESSION MODELS 1
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MULTIPLE REGRESSION MODELS 2
Assignment 1
Multiple regression models highlight the relationship between variables by fitting a linear
equation from the data observed. The value of x explanatory variable is associated with the y
explanatory variable. The data set that I will use is the General Social Survey 2006 to 2014.
There are 26 categories of variables. The population regression line in this case is
y
=
0
+
1
x
1
+
2
x
2
+ ... +
p
x
p
for the p explanatory variables x
1
, x
2
...
p
XP.
DATA = FIT + RESIDUAL
"FIT" represents
0
+
1
x
1
+
2
x
2
+ ...
p
x
p
.
Multiple linear regressions, given n observations:
y
i
=
0
+
1
x
i1
+
2
x
i2
+ ...
p
x
ip
+
i
for i = 1,2, ... n.
R-Square= (1-ratio of residual variability)
Response rates
Year
Response rate
Interviews
2006
71.2
4510
2008
70.4
2023
2010
70.3
2044
2012
71.4
1974
2014
69.2
2538
Mean
70.5
2617.8
Standard deviation
0.779744
967.9154

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Running head: MULTIPLE REGRESSION MODELS Student’s Name Professor’s Name Course Details Date 1 MULTIPLE REGRESSION MODELS 2 Assignment 1 Multiple regression models highlight the relationship between variables by fitting a linear equation from the data observed. The value of x explanatory variable is associated with the y explanatory variable. The data set that I will use is the General Social Survey 2006 to 2014. There are 26 categories of variables. The population regression line in this case is y = 0 + 1x1 + 2x2 + ... + pxp for the p explanatory variables x1, x2... pXP. DATA = FIT + RESIDUAL "FIT" represents 0 + 1x1 + 2x2 + ... pxp. Multiple linear regressions, given n observations: yi = 0 + 1xi1 + 2xi2 + ... pxip + i for i = 1,2, ... n. R-Square= (1-ratio of residual variability) Response rates Year Response rate Interviews 2006 71.2 4510 2008 70.4 2023 2010 70.3 2044 2012 71.4 1974 2014 69.2 2538 Mean Standard deviation 70.5 2617.8 0.779744 967.9154 MULTIPLE REGRESSION MODELS b0 = 101.22, b1 = 1.00, and b2 = 1.07 yi = 0 + 1xi1 + 2xi2 + yi = 101.22 + 1.00xi1 + 1.07xi2 The model will meet the assumptions given that the results support the Model for the General social survey on demographics. It also supports there is an impact of social change by demographic factors like age, income, and race. Moderation was significant because it showed decline demographic characteristics between 2006 and 2014.This b ...
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